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Microdata User Guide RESIDENTIAL TELEPHONE SERVICE

1. 3 5 3 3 3 2 3 2 8 450 kk ck ck Ck eee ee eee ee ck RR RA A A RA AAA A 3 2 3 0 2 9 2 7 500 kk ck ck Ck ROO Zn 2 9 2 8 2 5 750 OK Ck ck ck kk kk ke ke ROO ke kk ko ke OOOO OOOO OOOO OOOO RO A AA AA RRA AAA A gu 1000 FORO RR kk ke ke kk ROO kk kk ke kk ke ke kk kk kk kk ck ck kk ck ck ck kk ck ck kk ck ck Ok ko ck ck ck kk ck ck Ck kc k ck ck Ck ck ck ck Ck ck ck ck ck ck kck ck ck ck ck ck ck ck ck k ck Ck ck kck ck ck kok NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION 50 Special Surveys Division 70 0 N N CO 4 o Fn WwW P P S WG NS NN N Q Q iS S S S S 1 3 I t t OX Or O OO Co CO O O O O O O O O F F N N GQ Q E t O A ON O P I Q Ot OO O O 4 G Oy JAN XO S UI XO d O 00 X0 Q OY O0 O O xo OY I9 O0 O OI Q tio no WOW 90 0 PRPRPRPRN WORPNBAUY DMOPNWHRUDDEWUDAIANDVOOFPWHRADWDOWDENWHAUADWORPWUDAOWHOKRUODWWADOW O O p p m P P mp pP N NN NS N IS N WUU WU G Q Q S ds S I Q G O1 t 0101 0 O O OY O I I I OO OO 00 Residential Telephone Service Survey May 2003 User Guide RESIDENTIAL TELEPHONE SERVICE SURVEY May 2003 Approximate Sampling Variability Tables Atlantic Provinces NUMERATOR OF ESTIMATED PERCENTAG
2. TS T es 7 4 6 9 6 6 6 4 6 2 5 6 4 4 2 5 90 74 3 7 6 9 6 7 6 5 6 2 6 0 5 5 4 2 2 4 95 7 1 6 9 6 7 6 5 6 3 6 5 8 5 3 4 1 2 4 100 6 9 6 8 6 6 6 3 6 1 5 9 5 7 5 2 4 0 23 3 125 6 0 5 9 5 7 5 5 5 3 5 1 4 6 3 6 2 1 150 5 5 5 3 5 2 5 0 4 8 4 6 4 2 323 1 9 200 Ckckckckckckckckckckckckckckckckckckckckckck ck ck ckckckckckckckckckckck ck ck ck ck ckckckckck ko RR 4 6 4 5 4 3 4 2 4 0 NT 2 8 1 6 250 KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK ck ck ck k k kok kok kok ck ck ck ck KK kok 3k 4 0 3 9 3 7 3 6 sy d 5 300 Ok kk kk kk k kk kk kk kk kk kk kk kk ck kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck c
3. 9 5 9 2 9 0 8 7 8 4 8 1 7 8 Tal 545 342 7 9 2 9 0 8 7 8 4 8 1 7 8 7 5 6 9 5 3 S l 8 9 0 8 7 8 5 8 2 7 9 7 6 qus EF D 2 3 0 9 8 7 8 5 gt 8 0 NI 7 4 7 1 6 5 SO 2 9 20 Ckckckckckckckckckckckckckckckckckckckckckckckck ck ck ck ckckckckckckck ck KK KKK 8 3 8 0 7 8 Ta d 22 6 9 6 3 4 9 2 0 21 8 1 7 8 7 6 Pr F 6 8 6 2 4 8 2 49 22 Ckckckckckckckckckckckckckckckckckckckckckckckck ck ck ck ckckckckckckckck ck ck KKK 7 9 7 6 Post WA 6 9 6 6 6 0 4 7 DAN 23 Ckckckckckckckckckckckckckckckckckckckckckck ck ck ck ck ck ckckckckckck HH ck A KKK Ju 7 5 1 2 7 0 6 7 6 5 5 9 4 6 2 6 24 7 5 733 TaT 6 8 6 6 6 3 5 8 Mao 256 25 KKK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KK KKK ISA
4. 10 9 10 6 10 2 9 9 9 6 9 2 8 9 8 1 6 3 3 6 6 KKK KKK KKK KK KKK KKK KKK KKK ck ck ck ck ckckckckckckckck KK KKK 9 6 9 3 9 1 Bog 8 4 8 1 7 4 5 7 AS 7 8 9 8 7 8 4 8 1 q8 7 5 6 8 b d SL 8 Ckckckckckckckckckckckckckckckckckckckckckck ck KKK KKK KKK KKK KK KKK 8 3 8 1 7 8 7 6 7 3 7 0 6 4 5 0 2 9 9 KKK KKK KKK KKK KKK KKK KKK KK KKK KKK KKK KKK ck ck ck ck ck ck ckckck ko KKK 7 6 TOA Tl 6 9 6 6 6 0 4 7 2x4 0 Ckckckckckckckckckckckckckckckckckckckckckckckck ck ck KKK KKK KKK ck ck ck ck ckckckckck ko kk ok 72 7 0 6 8 6 5 6 3 Sr 4 4 2 6 ji Ok kk kk kk Sk kk kk kk kk kk kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK 6 7 6 5 6 2 6 0 5 5 4 2 2 4 2 Ok Ck kk kk kk kk kk kk kk kk kk ck kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK en 6 4 6 2 6 0 5 7 5 2 4 0 2 3 3 Ok kk Ck kk kk kk kk kk kk kk kk kk kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck k ck ck ck ck ck ck ck ck ck ck ck ck KK Pe 6 2 5 9 5 7 5 5 50 3 9 2 2 4 Ok kk kk kk kk kk kk kk kk kk kk kk ck kk kk ck ck Ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK en 5 7 5 5 5 3 4 8 Qu 2 52 5 Ok kk kk kk ok kk kk kk k
5. 8 2 8 0 7 8 7 5 7 3 7 0 6 7 6 1 90 k k k lt lt k lt k k k k ck k k k ck k k k ck ck k k ck K k K K K 8 0 7 8 ms uus 7 0 6 8 6 5 6 0 95 dE X deo oe de e e eee eee e oe E eee e ode ee 7 8 7 6 7 3 Laub 6 9 6 6 6 4 5 8 100 De ck kokck ck k k k k k k k ck k k Kk oko k 7 6 7 4 FT 6 9 6 7 6 4 6 2 561 125 6 8 6 6 6 4 6 2 6 0 5 8 545 541 150 6 2 6 0 5 8 5 7 5 5 5 3 5 4 6 200 5 2 SET 4 9 Z5 4 6 4 4 4 0 250 4 5 4 4 4 2 4 1 3 9 3 6 300 kk ck ck Ck kk kk kk kk kk AAA RRA AAA A e k ke 4 1 4 0 3 347 3 6 uod 350 3 7 3 6 3 4 3 3 3 0 400
6. 07 Oud 0 0 9 7 9 4 9 1 Bu 7 9 6 2 3 6 23 0 4 0 1 9 8 9 5 9 2 8 9 8 5 7 8 6 0 35 24 042 9 9 9 6 9 3 9 0 8 7 8 3 7 6 5 9 3 4 25 0 0 9 7 9 4 9 1 8 8 8 5 8 2 7 5 5 8 ke 30 9 1 8 9 8 6 8 3 8 0 7 8 EE 6 8 5 3 3 0 35 8 5 8 2 8 0 HET 7 5 7 2 6 9 6 3 4 9 2 8 40 7 5 Wen TO 6 7 6 5 5 9 4 6 2 6 45 7 2 7 0 6 8 6 6 6 3 6 536 4 3 2 5 50
7. 2 9 22 Dee 23 2 4 24 Zur 25 1 9 30 0 8 35 0 50 40 ck ck k k ck k k k k k k k k k k k k k k k k KKK 45 ck ck ck k ck k KK k k k k k k k k k k k k KKK 50 ck ck k k k k k k k k k k k k k k k k k k k AAA 55 ck k k ck k k k k k k k k k k k k k k k k k k KK 60 ck ck k k k k k k k k k k k k k k k k k k k KKK 65 ck ck k k k k k k k k k k k k k k k k k k k KKK 70 75 KKK KK k k k k k k k k k k k k k k k k k KK 80 ck k k k k k k k k k k k k k k k k k k k k KKK 85 ck k ck k K k k K k k k x k k k k k k k k k AAA 90 ck k k k k k k k k k k k k k k k k k k k k KKK 95 ck k k ck k k k k k k k k k k k k k k k k k k k x 100 ck ck ck k ck k k k k k k k k k k k k k k k k k k k k k k k k k k K 125 ck ck k k ck k k K k K k k K k k k k k K K k k k k k KKK KK 150 200 250 300 350 400 450 500 750 1000 1500 KK O
8. 6 9 6 7 6 5 6 2 6 0 5 8 S 4 1 224 55 6 6 6 4 6 2 5 9 yA 55 5 0 3 9 2 2 60 6 1 5 9 5 7 5 5 5 3 4 8 3o d 2 2 65 KKK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK ck ck ck ck ck ckckckck ko kk k 5 8 5 7 5 5 5 63 D 4 6 3 6 2 1 70 5 6 5 5 5 3 5 1 4 9 4 5 3 4 2 0 75 Ok Ck kk kk kk kk kk kk kk kk kk ck KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK en 5 3 5 1 4 9 4 7 4 3 3 43 9 80 Ok kk kk kk kk kk kk kk kk KA KK KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK zn 5 1 4 9 4 7 4 6 4 2 E 9 85 KK k k RK k k k k KR k k k k k k k k KO KK k k HH k k k k k k k k k k k k k k k k k k k k k k KK K 4 9 4 8 4 6 4 4 4 0 31 8 90 Ok Ck Ck kk kk kk KK kk kk kk KK ck kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck RK 4 8 4 6 4 5 4 3 3 9 3 0 8 95 Ok kk kk k
9. 5 4 5 2 5 1 4 9 4 8 4 6 4 4 4 0 3 8 75 5 2 5 1 4 9 4 8 4 6 4 4 4 3 3 9 3 0 ET 80 5 0 4 9 4 8 4 6 4 4 4 3 4 1 3 8 269 T 85 4 9 4 8 4 6 4 5 4 3 4 2 4 0 3 6 2 8 6 90 4 8 4 6 4 5 4 3 4 2 4 0 3 9 3 5 2T 6 95 4 5 4 4 4 2 4 1 3 9 Suig 3 4 2 7 P 100 4 4 4 3 4 1 de 3 8 Bust 3 4 26 25 125 30 3 8 7 3 6 3 4 33 3 30 2 3 v3 150 Ckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckck ck ck ck ck ck ck ckckckck kk kk 3 5 3 4 3 2 3v
10. 19 1 6 TTA 7 16 2 8 9 0 1 2 3 4 5 6 7 8 9 20
11. 5 4 5 3 5 1 4 9 4 7 2 3 3 3 9 80 Ckckckckckckckckckckckckckckckckckckckckckckckck ck ckckckckckckckckck ck ck ck ck ck ck ckckckck kk kk 5 3 5 1 4 9 4 7 4 6 4 2 s 2 9 85 ck ck k k k lt k k k k KA k k k RK k k k k k k k k k k k k k k k k k k k k k k k k k k kk k k K 5 4 9 4 8 4 6 4 4 4 0 3 1 8 90 Ok kk kk kk kk kk KK KK KK KK KK KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckock 4 8 4 6 4 5 4 3 3 9 3 0 8 95 Ok kk kk kk kk kk kk kk ck kk kk kk kk ck ck Ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK 4 7 4 5 4 3 4 2 3 8 3 0 7 100 Ok kk kk kk kk kok kk KA KK KK KA KK KK RK RRR RK 4 6 4 4 4 2 4 3 7 2 9 m 125 Ok kk kk kk ok kk kk kk kk kk kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK KK zn 3 9 3 8 3 6 3 3 2 6 5 150 Ok kk kk kk kk kk kk kk KK kk KK a a a a KK KA ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck kakak 3 5 3 3 3 0 2 4 4 200 Ok kk kk kk kk kk kk kk kk kk kk kk kk KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck Ck ck ck ck ck ck ck ck ck ck Ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck SDS 2 6 2 0 2 250 Ok kk kk KK RR RR 1 8 ST 300 Ok kk kk kk AAA KK A KK kk kk KK KK KK ck KA KK KA KK KK KK KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck
12. 2 1 22 23 24 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 125 150 200 250 300 KK ROK ROK ROK ROK OK RK k kok k RK RK RK RK ck ckck ck ck ckck ck ck ckck ck ck RARA ckck ck k ck ck ck ck ckck ck ck ck ck k ck ck ckck ck ck ckck ck ck ck ck kok ck ck ck ck ckck ck ck ck ck ck ck ck ck ckck ck ck ckck ck ck KEK NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION 48 40 0 50 0 70 0 33 30 23 6 23 21 16 1 19 T7 137 16 15 11 8 1 5 13 10 6 T3 TA 9 7 12 11 9 Ti 10 4 11 10 29 10 9 5 10 95 8
13. NN N N Q Q Q 4S S I O1 O1 O1 t t Oy OY OY O d O0 OO o XO O O O O P pP p N G Q d Gn O d 0 w SQ Oi XO 4S tO O Q wo Q S OY OO iS 0 Q OO O F S iS O OO ON O1 O N ano Jl 2 CkCkckckckck ck kckck ckck ck k ck k ck k ck k ck k ck k ck k ck kck k ck kckck ck k ck kckckckckckckckckckckckck ck kckckckckckckckckckckckckck ck ckckckck ck ck ckck ck ck ckck ck ok CKCkckckckck ck kckck ck k ck k ck k ck ck ck k ck k ck k ck k ck k ck k ck k ck k ck kckck ck kckck ck k ck kckckckckckckckck ck kckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckck ck ck ck ck ck ck PERCENTAGE 000 0 1 1 0 2 0 1 59 9 59 6 59 3 2 42 1 41 9 3 34 4 34 2 4 FOO 29 8 29 6 5 26 7 26 5 6 24 3 24 2 7 2245 22 4 8 OO OO 21 1 21 0 9 9 9 9 8 0 8 8 Br 1 8 0 7 9 2 Tea TEL 3 6 5 6 4 4 5 9 5 8 5 5 4 5 3 6 4 9 4 8 7 4 5 4 4 8 4 0 4 0 9 3 7 3 6 20 3 3 2 1
14. 6 3 O Q 4 Ul OY d O O HQ Ui J O Q 1 EN 00 O QQ Ui J XO gt 4S OY XO QQ RARA O QG O gt ES ES Q dS UI Oy O XO Q O O0 I9 O S BAUN Oo O S 4S OY x0 N O1 O N IV 00 O1 O1 H Q OO U Q C Q Q Q Q Q S uS uS S dS I 1 t O OY OY N yN J co OO OO OO tO N Q Q Q Q Q Q Q Q QQ S dS dS S t Qn 0 O1 OY O OY O d d O0 OO oo N a N Cn p p p I N DO IO I9 GS NN N 0 0 Q Q ds uS S uS dS 01 01 t O1 O1 O1 O1 O Ov OY O NN 0 o OUD O PS d d OU Or O d OO Q0 LO N Q OU d O Q d O0 tO O S Q gt DIO Special Surveys Division 90 0 N S S S NN N N Q Q Q WW WWW S S S O1 n OY Oy 0 Q XO O P M dS 4S S 01010009010 O WAUN O O0 O O N Q iS Gn O O x0 Q O O I9 O 0 JJ Residential Telephone Service Survey May 2003 User Guide RESIDENTIAL TELEPHONE SERVICE SURVEY May 2003 Approximate Sampling Variability Tables Alberta NUMERATOR OF ESTIMATED PERCENTAGE PERCENTAGE 000 0 1 1 0 2 0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 70 0 90 0 T 1342 72 9 12 5 71 4 69 5 67 5 65 5 63 4 61 3 5941 56 7 51 8 40 23 2 2 AR ROR IA 53 55 51 3 50 5 49 1 47 8 46 3 44 9 43 3 41 8 40 36 6 28 4 16 4 3 AS HRS TRIES IE 42 1 41 9 41 2 40 1 39 0 37 8 36 6 35 4 34 1 32 8 29 9 23 2 13 4 4 ERRATA E 36 4 36 3 35 7 34 7 33 8 32 8 3147 30 6 2955 28 4 25 9 20 11 6
15. P 6 9 6 7 6 5 6 2 Sl 4 4 2 5 30 KKK KKK KKK KKK KKK KKK KKK ck ck ck ckckckckckckckckckck ck ck ck KK ck ck ckckck kk kk 6 5 6 3 6 1 5 9 57 52 4 0 2 3 35 6 1 5 9 5 7 5 5 5 2 4 8 Sab 2 A 40 Ok kk kk kk kk KK KK kk kk kk KK KK KK ck ck ck ck ck ck ck ck ck ck ck ck KR 5 5 5 3 5 1 4 9 4 5 305 2 0 45 Ok kk kk KA KA KK KK KA KA KA KK KK ck ck ck ck KK KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK 5 2 5 0 4 8 4 6 4 2 3 3 9 50 Ok Ck Ck kk kk kk kk KK KA a a KA KK kk ck kk ck KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK 4 7 4 6 4 4 4 0 3 1 8 55 Ok kk kk kk kk kk kk kk kk ck kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck k k k 4 5 4 4 4 2 3 8 3 0 7 60 Ok kk Ck kk kk kk kk kk kk kk kk az KA KK KA KK ck ck een 4 2 4 0 3 7 2 8 6 65 Ok kk Ck kk kk kk kk kk kk kk kk kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck kckck 4 0 3 9 3 5 2g 6 70 Ok kk Ck kk kk kk kk kk kk kk ck kk ck ck ck ck ck ck KA ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK e
16. the primary sampling unit Apartment buildings are sampled from the list frame with probability proportional to the number of units in each building Special Surveys Division Residential Telephone Service Survey May 2003 User Guide Within each of the secondary strata in rural areas where necessary further stratification is carried out in order to reflect the differences among a number of socio economic characteristics within each stratum Within each rural stratum Six EAs or two or three groups of EAs are sampled as clusters 5 2 5 Dwelling Selection In all three types of areas urban rural and remote areas selected clusters are first visited by enumerators in the field and a listing of all private dwellings in the cluster is prepared From the listing a sample of dwellings is then selected The sample yield depends on the type of stratum For example in the urban area frame sample yields are either six or eight dwellings depending on the size of the city In the urban apartment frame each cluster yields five dwellings while in the rural areas and EA parts of cities each cluster yields 10 dwellings In all clusters dwellings are sampled systematically This represents the final stage of sampling 5 2 6 Person Selection Demographic information is obtained for all persons in a household for whom the selected dwelling is the usual place of residence LFS information is obtained for all civilian household members 15 years of
17. was your total annual household income before taxes and deductions less or more than LICO FREQ WTD 1 Less than 8 283 2 634 594 2 More than 27 264 8 307 147 7 Don t know 2 807 815 223 8 Refused 1 545 425 328 9 Not stated 25 9 014 39 924 12 191 305 Coverage All respondents 70 Special Surveys Division Residential Telephone Service Survey May 2003 User Guide Residential Telephone Service Survey May 2003 Public Use Microdata File Section Weight Variable Variable Name FINWT Position 20 Length 9 4 Weight Format 9 4 Physical decimal present 9999 9999 Section Demographic Variable Variable Name SZCODE1 Position 29 Length 1 Size of area of residence FREQ WTD 1 Urban population of 500 000 or more 10 126 6 094 605 2 Urban population of 100 000 499 999 9 706 1 920 659 3 Urban population of 30 000 99 999 3 672 971 731 4 Urban population of 15 000 29 999 2 266 401 235 5 Urban population under 15 000 5 019 1 011 607 6 Rural areas 9 135 1 791 468 39 924 12 191 305 Variable Name SZCODE3 Position 30 Length 2 Size of area of residence FREQ WTD 10 Urban population of 500 000 or more 10 126 6 094 605 20 Urban population of 100 000 499 999 9 706 1 920 659 30 Urban population of 30 000 99 999 3 672 971 731 40 Urban population of 15 000 29 999 2 266 401 235 51 Urban population of 2 500 14 999 3 893 781 375 52 Urban population under 2 500 1 126 230 231 60 Rural areas
18. 1i 3 0 EN 251 a2 200 KKK KKK KR KK RK KR RR RR ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK KK 2 9 2 8 DE 2 6 2 4 1 8 1 250 Ok kk kk kk k k kk kk kk kk kk kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK 2 5 2 24 2053 2 1 1 6 0 300 Ok kk kk kk KA kk ok KK KK K KA KK KK KA KK KK KK KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck kk Dd DT 1 9 LoS 0 9 350 Ok kk kk kk KA KA KA KA KA KA KK KA KA KA KA ck ck KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck AEE 2 0 1 8 T4 0 8 400 Ok Ck kk kk kk kk kk kk kk kk kk kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck kckck 1 7 1 3 0 8 450 Ok kk kk kk kk kk Sk kk kk kk kk kk ck KA KA ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck Ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckock 1 6 2 0 7 500 Ok kk kk kk KA Sk kk kk kk kk kk kk ck KK KK ck KK KK ck ck ck KK KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckck t gt I 750 Ok kk kk kk Sk
19. 2 25 Wok oko t 19 4 9 0 8 7 842 7 7 T 6 6 6 0 55 4 9 3 6 0 5 6 1 30 ES RARE K 17 4 TES Jg 6 6 6 1 5x 9 2 4 6 4 1 3 6 2 4 9 6 Sn 35 ERE AREAL RAIA AA A 6 0 5 8 5 4 4 9 4 5 4 0 3 6 3 2 2 6 1 25 8 9 Dyck 40 RAKE ROLLA LEAS KEK 5 0 4 8 4 4 4 0 3 6 Su 2 7 2 2 TA 0 7 8 3 4 8 45 WO Auc pus RA kae opes 4 2 3 09 3 6 3 2 2 8 2 4 2 0 1 85 TET 0 7 8 4 5 50 ERA E ERE ER ee dee 3 4 S2 2 9 2 5 2 1 1 57 ToS 0 9 0 5 9 6 7 4 4 3 55 RAT JONG E 2 8 2 6 253 1 59 1 6 142 0 8 0 4 0 0 93 7 4 1 60 a 243 2 1 du 1 4 lom 0 7 0 4 0 0 9 6 8 8 6 8 39 65 1 6 1 3 1 0 0 6 03 0 0 9 6 9 2 8 4 6 5 3 8 70 Ok Ck Ck kk kk kk KK KKK KKK KKK kok kok 12 0 9 0 6 0 3 9 9 9 6 9 2 8 9 8 6 3 3 6 45 PFA EEFKES EEEE A KK Ko KO UK 0 8 0 5 0 2 9 9 9 6 953 8 9 8 6 7 8 6 35 80 KKK KKK KKK KA KK KK kk ck ck kk KKK 0 5 0 2 9 9 9 6 9 3 9 0 8 6 8 3 7 6 5 9 3 4 85 0 1 9 9 9 6 9 3 9 0 Beg 8 4 B 7 4 5 7 3439 90 Ok Ck Ck kk kk kk kk kk KK KK kk kk kk k 9 9 9 6 9 3 9 0 8 8 8 5 8 2 7 8 7 5 5 3 2 95 22 akuna EO nn 9 6 9 3 9x 8 8 8 5 8 2 TaJ 7 6 7 0 5 4 Su 100 ARE RR xo RAEN ow RR eos 9 3 9 1 8 8 8 6 8 3 8 0 EI 7 4 6 8 5 3 3 0 125 Ok kk kk kk kk kk kk kk KKK KKK ck ko 8 4 8 1 7 9 TF 7 4 pr 6 9 6 6 6 4 7 2 7 150 JI KOCKOCKUE EEA AERA ER ii 7 6 7 4 7 2 7 0 6 8 6 6 6 3 6 eal 5 3 4 3 2 5 200 Ok Ck Ck Ck kk KKK KK KK KK KK KKK
20. 2 4 7 4 2 3 6 2 4 9 6 56 0 Sk 6 2 5 8 5 4 4 9 4 4 3 9 3 4 2 9 1 8 9 1 53 1 5 5 5 1 4 6 4 2 3 8 3 3 2 8 2 3 1 2 8 7 5 0 2 EBERLE LAA AER AR RE 4 8 4 4 4 0 3 6 3 2 2 7 243 1 8 0 8 8 3 4 8 3 F 2 3 9 3 5 3 1 257 2 2 1 8 143 0 3 8 0 4 6 4 Ou 3 4 3 0 2 6 2 2 1 8 1 4 0 9 0 0 Ju 4 5 9 RR NE RRL AK RAR eA A gus 2 9 2 5 2 2 1 8 1 4 1 0 0 5 9 6 7 5 4 3 6 EAN RAE BEA ARAM 2 8 24 5 271 T48 1 4 1 0 0 6 0 2 933 7 2 4 2 7 lt k lt ck k k k ck k k k k k k k k k k k k k K 2 5 2 4 1 8 1 4 dread 0 7 04 3 9 9 9 0 7 0 4 0 8 2 1 8 1 5 Tb 0 8 0 4 0 0 9 6 8 8 6 8 349 9 1 5 11 0 8 0 5 021 9 7 9 4 8 5 6 6 NS 20 1 2 0 9 0 5 0 2 9 9 9 5 9 1 8 3 6 5 Ou 21 0 9 0 6 0 3 0 0 9 6 9 3 8 9 8 1 6 3 3 6 22
21. 25 7 23 230 1 6 1 2 0 8 0 4 9 5 Ts 4 2 35 2 1 27 1 4 TG 0 7 0 4 0 0 9 6 8 8 6 8 3349 40 1 3 1 0 0 7 0 4 0 0 9 7 9 3 9 0 8 2 663 3 7 45 0 6 0 4 0 9 8 9 5 9 1 8 8 825 7 7 6 0 35 50 KOK ROK ROK ROK kckck ck kckck ck k ck KA KA ok 0 1 9 8 9 6 9 3 9 0 8 7 8 4 8 0 T lt b uS 55 RAKE KER AEA KERRI RRA 9 6 9 4 95 8 8 8 6 8 3 8 0 Tat 7 0 5 4 3 1 60 9 0 8 7 8 5 8 2 7 9 7 6 7 3 6 7 5 2 3 0 65 8 6 8 4 8 1 7 9 7 6 TES 7 0 6 4 5 0 2409 70 8 3 8 AO 7 6 7 3 Ls 6 8 6 2 4 8 2 8 75 8 0 7 8 7 6 7 3 7 1 6 8 6 6 6 0 4 6 24 80 7 8 7 6 x 7 Fall 6 9 6 6 6 3 5 8 4 5 2 6 85
22. 3 729 1 624 276 39 924 12 191 305 Special Surveys Division Residential Telephone Service Survey May 2003 User Guide Residential Telephone Service Survey May 2003 Public Use Microdata File Variable Name CMA1 Position 3 Length 2 Census Metropolitan Area FREQ WTD 00 Non CMA 26 549 5 186 400 01 Halifax 601 142 007 02 Quebec 560 305 512 03 Montreal 1 573 1 519 024 04 Ottawa 643 354 029 05 Toronto 1 997 1 753 562 06 Kitchener 547 152 572 07 Hamilton 558 279 311 08 St Catharines 597 166 138 09 London 563 175 965 10 Windsor 464 121 147 11 Winnipeg 1 406 282 836 12 Calgary 885 353 975 13 Edmonton 1 244 398 988 14 Vancouver 1 249 845 082 15 Victoria 488 154 756 39 924 12 191 305 Section Telephone Service Variable Variable Name Q01B Position 5 Length 1 How many different telephone numbers are there for your residence Include cellular phone numbers and phone numbers used for business 0 None 4 2 3 or more OD Coverage Allrespondents FREQ WTD 587 156 109 22 817 6 707 406 39 924 12 191 305 64 Special Surveys Division Residential Telephone Service Survey May 2003 User Guide Residential Telephone Service Survey May 2003 Public Use Microdata File Variable Name Q01C Position 6 Length 1 Is this number for a cellular phone or Are all of these numbers for cellular phones FREQ WTD 1 Yes 671 232 969 2 No 38 631 11 793 474 6 Valid skip 587 156 109 7 Don t kn
23. 39 2 30 3 IE e 4 MERER eoe 47 7 47 5 46 7 45 5 44 2 42 9 41 5 40 38 7 37 1 33 9 26 3 19552 5 LAR AAR 42 7 42 5 41 8 40 7 39 5 38 4 37 1 3549 34 6 39 2 30 3 23 20 13 6 6 ukt BA 39 0 38 8 38 2 SU d 36 1 390 33 9 32 8 31 6 30 3 Zed 21 4 12 4 7 kasuk sassa 36 1 35 9 35 9 34 4 33 4 32 4 31 4 30 3 2972 28 1 25 6 9 29 130 5 8 A 33 7 33 6 33 0 32 2 31 3 30 3 29 4 28 4 27 3 26 3 24 0 8 6 10 7 9 OK DOES 3148 31 6 31 2 30 3 29 5 28 6 2 s 26 7 25 8 24 8 22 6 dn 10 0 DS RAS OE 30 2 30 0 29 6 28 8 28 0 2 y 26 3 2544 24 5 239 21 4 6 6 9 6 1 REEA Noe 28 8 28 6 28 2 27 4 26 7 25 9 25 0 24 2 23 3 22 4 20 4 5 8 9 2 Se EAE 2a 27 4 27 0 26 3 25 5 24 8 24 0 23 2 22 3 21 4 9 6 952 8 8 3 RARAS 26 5 26 3 25 9 2552 24 5 23 8 23 0 22253 21 4 20 6 8 8 4 6 8 4 4 BAERS Ee 255 25 4 25 0 24 3 23 6 22 9 22 2 21 4 20 7 9 9 8 1 4 0 8 5 ER KARE ICE 24 6 24 5 24 29 5 22 58 22 51 21 4 20 7 20 0 92 7 5 3 6 7 8 6 a UK 23 9 23 7 23 4 22 7 22 1 21 4 20 8 20 9 3 8 6 7 0 Sud 7 6 4 ARA 23 1 23 0 2251 2241 21 4 20 8 20 43 95 8 8 8 0 6 4 251 7 4 8 e bad 22 5 22 4 22 0 21 4 20 8 20 2 9 6 8 9 8 2 E 6 0 2 4 Ue 9 BERE Kee 21 59 21 8 21 4 20 9 20 3 9 7 9d 8 4 gus 7 0 5 6 Ql Ed 20 a eo e 21 3 2132 20 9 20 3 9 8 972 8 6 19 7 3 6 6 342 1 7 6 8 21 ARAN 20 8 20 7 20 4 949 973 8 7 8 1 T S 6 9 6 2 4 8 T5 6 6 22 d d 20 3 20 2 9 9 9 4 8 9 8 3 Td E 6 5 958 4 5 1 2 6 5 23 kasu RANE 19 9 9 8 9 5 9 0 8 4 7 9 Txa Gal 6 1 5 5 4 1 0 6 3 24 SR eoa T1945 9 4 9 8 6 8 0 7 5 7 0 6 4 5 8 532 3 8 0 7 6
24. 5 7 Sal 3 8 0 7 6 2 8 BERATER 8 9 8 8 8 5 8 0 T5 7 0 6 4 0 9 543 4 7 3 4 0 4 6 0 9 AREA REARS 8 4 8 3 8 0 7 5 7 0 6 5 6 0 5 5 4 9 4 3 33 0 5 8 20 a 7 9 7 8 7 5 Her 6 6 6 1 5 6 Sal 4 5 349 2 7 9 9 5 31 21 WO RU Ee NIE 7 4 quu 6 7 6 2 Du S 2 4 7 4 2 3 6 2 4 9 6 5 6 22 Wh ER le UO 6 7 6 3 2 8 5 4 4 9 4 4 3 8 3 53 2 9 4 5 4 23 KARA ORO 6 7 6 6 6 4 5 9 5 5 5 0 4 5 4 0 3 5 3 0 1 59 9 2 Sy 24 IA 6 4 6 3 6 0 5 6 952 4 7 4 2 3 8 343 257 1 6 9 0 9 2 25 Wok Meo 6 0 5 9 5 7 523 4 8 4 4 3 9 Bio 3 0 225 1 4 8 8 5 1 30 WERE 4 6 4 6 4 3 Sui 3 6 ST VRAT 2 3 1 9 1 4 0 4 8 4 6 35 BREA ck 3 25 35 3 3 2 9 2 5 2 2 Tog 1 4 1 0 0 5 9 6 7 5 4 3 40 TOR AEE 2 7 2 6 2 4 240 TA 1 4 1 0 0 7 0 3 9 9 9 0 7 0 4 0 45 ERA RL 1 1 9 coy 1 4 1 1 0 7 0 4 0 0 DET 9 3 8 5 6 6 3 8 50 FERINA 1 03 Vsa 1 5 0 8 0 5 0 2 959 9 5 952 8 8 8 6 2 3 6 55 A Xo 0 8 0 7 0 6 0 3 0 0 957 9 4 Os 8 8 8 4 7 7 5 9 3 4 60 ARE A 0 3 0 3 0 9 9 9 6 9 3 9 0 8 7 8 4 Bud 7 4 Dia 1 I 65 e SSO W S 9 9 947 955 972 8 9 8 6 8 4 8 1 WERT Jd 9 5 3 2 70 KEANE 9 6 9 5 9 4 9 1 8 9 8 6 8 3 8 7 8 7 5 6 8 9 3 3 0 45 ARIANE 9 3 9 2 95 8 8 8 6 8 3 8 7 8 YA 7 2 6 6 Sal 2 9 80 FERRARI 9 0 8 9 8 8 8 5 8 3 Bud 7 8 Tan Tas 7 0 6 4 4 9 2 8 85 de Be 8 7 8 6 8 5 8 3 8 1 7 8 7 6 7 3 7 0 6 8 6 2 4 8 2 8 90 ERRANEAS 8 4 8 4 8 3 Pek 7 8 7 6 7 4 7 6 8 6 6 6 0 4 6 2 95 A 8 2 8 2 8 7 8 7 6 7 4 7 2 6 9 6 7 6 4 5 8 4 5 2 6 100 AAA 8 0 8 0 7 8 7 6 7 4 7 2 7 0 6 7 6 5 6 2 Sis 4 4 25 5 125 do RE EE 7 0 6 8 6 6 6 4 6 2 6 0 248 5 6 Sa
25. 6 4 ou 3 3 3 0 2 6 2 2 1 8 Tes 0 9 9 9 TA 4 4 9 PEKA E EREE Ski ER RARE AA ORO 3 2 2 9 2 5 2 1 1 8 1 4 0 9 0 5 9 6 7 4 4 3 6 aa IO A 2 8 2 9 2 1 8 1 4 1 0 0 6 0 2 943 7 2 4 2 7 Okckckckckckck ck ckokck ck Kk k k k k k k k k k ke 2 4 Da 1 8 1 4 1 0 0 7 0 3 9 9 9 0 7 0 4 0 8 VIN 1 8 1 4 TL 0 7 0 4 0 0 9 6 8 8 6 8 34 9 9 1 8 1 4 I 0 8 0 4 051 9 7 9 3 8 5 6 6 3 8 20 ER RA ARE LOR A HR KK RRR Ue 1 9 1 2 0 8 0 5 0 2 9 8 95 5 93d 8 3 6 4 3 21 Ok ooo o I I IOI ioo 1 2 0 9 0 6 0 3 9 9 9 6 9 2 8 9 8 1 6 3 3 6 22 0 6 0 3 0 0 9 7 9 4 9 0 B 7 9 6 1 3ie5 23 K k lt k k k k k 1k k k k k k k k k k k k k k k K k K k ke K ke 0 4 0 9 8 9 5 9 2 8 8 8 5 7 8 6 0 345 24 koe kop di Kp Kao KK Rok kx A RN Koo eoe 0 2 9 9 9 6 943 9 0 8 7 8 3 7 6 3 9 3 4 25 0 0 9 7 9 4 9 1 8 8 8 5 83 7 4 5 8 3 3 30 Ckckckckckckckckckckckckckckckckckckckckck ck ck ck ck ck ck ck ck ck HE 9 8 8 8 6 8 3 B0 FLT 7 4 6 8 55 9 3 50 35 K K k lt k k k k k 1k k k k k k k k k
26. 8 17 13 15 Tale 13 10 12 10 12 9 Ir 10 10 9 OO XO ON Q UO OY OO O 2 OY tO Q O0 UI OY OO xo QQ Ui OO O O O 0 I9 O 4s N P N O G AW C CO gt uS ds dS aS uS UI UI O1 O1 OY O N N O XO O O O F F N 0 4S G OS w Ss UI OY OO o S S OY OO gt 00 S OO i0 Q iS 0 OO O 0 01 00 8 00 0 OO QQ O O QO N O 0 S O Q C Q Q Q Q dS ds S uS uS UI O1 O1 OY OY O d N HAN O0 0 OO CO o o w o VO N IS OS O0 Q0 0 O Q i Oy XO N O1 O0 Q iS U1 OY O O O I0 PAD O GQ OY XO 0 OO 0 O 00 00 NM NM O iS Pb N S ON MON IS NW YU YY GQ Q 4S ds ds 0101 0101 0101 OY O1 OY OY Oh IA J 1 CO CO Special Surveys Division 90 0 RR oo wm NNNNNNNO CO CJ CO Q CO Y CO Q WU ds ds ds ds uS 01 O1 O1 O O O P S i gt Q Or oO l loo0t00Hn N G gt O O O P N S GI O 10 O Nd 00 gt 0 NO 0 0 0 m Residential Telephone Service Survey May 2003 User Guide RESIDENTIAL TELEPHONE SERVICE SURVEY May 2003 Approximate Sampling Variability Tables Quebec NUMERATOR OF ESTIMATED PERCENTAGE PERCENTAGE 000 0 1 1 0 2 0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 70 0 90 0 1 95 9 95 4 94 9 99 55 91 0 88 4 85 8 83 1 80 2 TAES 74 3 67 8 52 5 30 3 2 67 8 67 5 67 1 66 1 64 3 62 5 60 7 58 7 56 7 54 7 92 5 48 0 Sed 21 4 3 5543 SS le 54 8 54 0 52 5 51 0 49 5 48 0 46 3 44 6 42 9
27. CI 0 567 2 0 567 0 056 0 567 2 0 567 0 056 CI 0 567 0 064 0 567 0 064 CI 0 503 0 631 With 95 confidence it can be said that between 50 3 and 63 1 of households which did not have telephone service for their residence during the reference period reported that they could not afford telephone service 10 3 How to Use the Coefficient of Variation Tables to Do a T test Standard errors may also be used to perform hypothesis testing a procedure for distinguishing between population parameters using sample estimates The sample estimates can be numbers averages percentages ratios etc Tests may be performed at various levels of significance where a level of significance is the probability of concluding that the characteristics are different when in fact they are identical Special Surveys Division 39 40 Residential Telephone Service Survey May 2003 User Guide Let X and X be sample estimates for two characteristics of interest Let the standard error on the difference X X be o A A If t XX G is between 2 and 2 then no conclusion about the difference between the characteristics is justified at the 5 level of significance If however this ratio is smaller than 2 or larger than 2 the observed difference is significant at the 0 05 level That is to say that the difference between the estimates is significant 10 3 1 Example of Using the Coefficient of Variation Table
28. Du 4 6 3 53 9 A E 8 2 7 9 7 4 6 9 6 4 5 9 533 4 8 4 2 3 0 20 ERN ka LAR Kul T 7 4 7 0 6 5 6 0 555 540 4 4 3 8 2 6 21 ORG Ken dae e opa oae Tea 7 0 6 5 6 5 6 Sud 4 6 4 1 3 5 2553 2 kuk aaa ab aaa 6 9 6 6 6 2 Del 9 2 4 8 4 3 3 7 3 2 2 0 23 SERA AA GRON UR E AOI EUR 65 6 2 5 8 5 4 4 9 4 4 3 9 3 4 2 9 1 8 24 FAA RAE SAE Ke 6 2 5 9 5 5 54 0 4 6 4 1 3 7 342 2 6 1 5 25 NORD NOR EO KURSE 5 8 5 6 5 2 4 7 4 3 3 8 3 4 249 2 4 143 30 BS FAIA RIK Stan Sa 4 4 4 2 3 8 3 5 S T 2 6 2 2 1 8 1 3 0 3 35 Kk kckckckckckckck ck k k k ck k k k ck ck k k k k 3 2 Dg Dy 2 1 T 1 3 0 9 Q5 9 6 40 2 3 2 0 1 57 1 33 0 9 0 6 0 2 9 8 8 9 45 Okckckckckckck ck ckokck ck k k k k k k k k k k ke 1 6 T3 1 0 02 7 0 3 0 0 9 6 9 2 8 4 50 1 0 OU 0 4 0 1 9 8 9 5 9 1 8 8 8 0 55 RAR AK KE e ERA SELLER koe RE 0 5 0 2 9 9 9 6 93 3 9 0 8 7 8 3 7 6 60 A K k k ck k k k ck k k k ck k k k ck k k k k k k K 0 1 9 8 9 5 9 2 8 9 8 6 8 3 8 0 TuS 65 K k lt k k k k k k k k k k k k k k k k k k e 9 7 9 4 9 1 8 9 8 6 8 3 8 0 TEE Ts 70 Ckckckckckckckckckckckck ck ck ck ck ckckck ck kk kk 9 3 9 1 8 8 8 5 8 3 8 0 7 7 7 4 6 8 AS SERN ARLEN AS ERA A RE 9 0 8 8 8 5 8 3 8 0 747 7 4 74 6 5 80 8 7 8 5 8 2 8 0 AT Tu 7 2 6 9 6 3 85
29. O QG PP O G 0 O P OS CKOkckckckck ck k ck k ck kckck ck k ck k ck k ck kckckckck ck kckckckckckckck ck ckck ck ck ckck ck ROK RK RT CKCkckckckckckckckck k ck ck k ck k ck k ck kckck ck k ck k k KA KA KA KA KA KA kok k k ck ck ck ck ck CKCkckckckck ck ck ck k ck k ck kckckckck ck KA KA KA KA KA KA KA KA KA KA KA ck ck ck sk 36 ck ck CKCkckckckck ck kckck ck kckckckck ck k ck kckck ck KA KA KA KA KA KA KA KA ck ckck ck ck ck ck ck ck 20 0 38 2 22 o B O Q BP O D O OY O0 WW QQ QO OS SS UI UI O1 O1 OY O J N J O0 OO O0 O0 OO iO o io O O O P P N N QG BON N gt o O ox oo O M Qn oo 5 CKCkckckckckckckckck ck kckck ck k ck k ck kck k ck kckck ck k ck kckckckckckckckck ck kckckckckckckckck ck KA AAA CKCkckckckckckck ck k ck kckck ck k ck k ck k ck k k k kok ck k ck KA KA KA KA KA k kok k KA KA KA ck ck ck ck ck k ck CKCkckckckckckck ck k ck k ck k ck k ck kckck ck kckckckck ck KA KA KA KA KA KA KA KA KA KA KA ck ck ck kk ck ok CKCkckckckckckckckck ck k ck kckckckck ck k ck k ck KA KA kckckckckckck ck KA KA KA KA KA KA ck ck ck ckck ck ck ck ok 25 0 37 26 2L w Q gt uS uS ds dS S O1 UI O1 O1 OY O JJOO iO XO O O O IP BF N Q 4S G OS O P2 N Q Gn O OO O 2 Oy tO Q OO UI OY O O S i gt OY O0 PB Q O S 00 QO OO O1 N H WAND gt aS CKCkckckckckckckckck ck k ck kckck ck k ck k ck k ck k ck k ck kckckckckckckckckckck ck k ck kckckckckck
30. RARE NENNE 19 5 9 0 8 5 17 9 17 4 16 8 16 2 15455 14 2 11 0 6 3 5 ARAS EGER AAA OR Bate CORREDOR 1795 7 0 6 5 16 0 15 455 15 0 14 5 13 9 127 9 8 5 6 EA 16 0 5 5 9 14 6 14 2 13 7 13 2 1233 li 6 9 0 5 52 7 RAPA NS AAR RIA OR Ue OK KR OR RO 14 8 4 4 4 0 13 6 13 1 12 27 12 2 EEE 19 57 8 3 4 8 8 kapa AA IEA A AK s s 13 8 3 4 9 12 7 125 3 11 9 11 4 11 0 10 0 Lag 4 5 9 i pK aC AN 13 0 251 2543 12 0 11 6 14 2 10 8 10 4 9 4 7 3 4 2 0 2 0 127 11 53 11 0 10 6 10 2 9 8 9 0 6 9 4 0 ji 1 5 1 10 8 10 5 TOZXT 9 7 9 4 8 5 6 6 3 8 2 1 0 0 7 10 4 10 0 9 7 9 3 9 0 8 2 6 3 Sue 3 0 5 0 3 9 9 9 6 9 3 9 0 8 6 7 9 6 1 345 4 05 2 9 9 9 6 9 3 9 0 8 6 8 3 26 5 9 3 4 5 9 8 9 5 9 3 9 0 8 7 8 3 8 0 ES Sra 6
31. RESIDENTIAL TELEPHONE SERVICE SURVEY May 2003 Approximate Sampling Variability Tables Manitoba NUMERATOR OF ESTIMATED PERCENTAGE PERCENTAGE 000 0 1 1 0 2 0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 70 0 90 0 1 AA 52 3 52 0 51 52 49 9 48 5 47 0 45 5 44 0 42 4 40 7 Flak 28 8 16 6 2 EAS 37 0 36 8 36 2 35 3 34 3 33 2 32 2 3s 30 0 28 8 26 3 20 4 11 8 3 US ASE Ad 30 2 30 0 29 6 28 8 28 0 27 1 26 3 25 4 24 5 23 5 21 5 16 6 9 6 4 has er REE 26 2 26 0 25 6 24 9 24 2 23 5 22 8 22 0 21 2 20 4 8 6 14 4 8 3 5 EROR OK ARAL ES KG SK 23 3 22 9 2253 21 7 21 0 20 4 941 9 0 8 2 6 6 12 9 7 4 6 a LL ta EEEE 212 2 079 20 4 9 8 9 2 8 6 8 0 7 3 6 6 5 2 11 8 6 8 7 EORR RR AA 19 7 9 4 8 8 8 3 7 8 7 2 6 6 6 0 5 4 4 0 10 9 6 3 8 EAA Kok E OK E REA EEE 18 4 8 1 7 6 7 1 6 6 6 95 5 5 0 4 4 Su 10 2 9 9 9 god 6 6 6 2 5 7 5 2 ET 4 1 3 6 2 4 9 6 545 0 6 2 5 8 5 3 4 9 4 4 3 9 3 4 2 9 1 8 9 1 5d 1 5 4 5 0 4 6 4 2 3 7 3 3 2 8 2 3 1 2 8 7 5 0 2 SE RA AR OS KK ETA PEER 4 8 4 4 4 0 3 6 3u 2 7 2 42 1 8 0 7 8 3 4 8 3 4 2 3 8 3 4 3 0 2 6 2 2 1 8 143 0 3 8 0 4
32. USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION 36 Special Surveys Division Special Surveys Division Residential Telephone Service Survey May 2003 User Guide 2 Using Rule 3 the standard error of a difference l X is oi Ja as i where X is estimate 1 Quebec X is estimate 2 Ontario and and are the coefficients of variation of x and X respectively That is the standard error of the difference given A d 0 257 0 190 0 067 is c 0 257 0 028 0 190 0 035 0 0000517 0 0000442 0 0098 3 The coefficient of variation of d is given by 0 1d 0 0098 0 067 0 146 4 So the approximate coefficient of variation of the difference between the estimates is 14 6 which is releasable with no qualifications Example 4 Estimates of Ratios Suppose that the user estimates that 796 352 households in Quebec reported that their total annual income was less than the low income cut off LICO while 858 163 households in Ontario reported that their total annual income was less than LICO The user is interested in comparing the estimate of Quebec households versus that of Ontario households in the form of a ratio How does the user determine the coefficient of variation of this estimate 1 First of all this estimate is a ratio estimate where the numerator of the estimate x is the number of households in Quebec which reported that the
33. ck ck ck ck ck ck ck ck KK zn 2 6 2 5 2 5 2 4 2 3 DEN 1 6 0 9 1000 gt i R 20 2 0 1 8 1 4 0 8 1500 Ok Ck kk kk kk kk kk kk kk kk kk kk ck KK ck ck KK ck ck KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK TAT 1 26 1 5 1 0 7 2000 Ok kk kk kk kk kk KA KA KK KK kk ck kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck OKE 1 3 1 0 0 6 3000 Ok kk kk kk kk kk kk kk kk kk ck kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck kckck 0 8 0 5 4000 Ok Ck Ck kk kk kk kk kk kk kk kk kk ck ck ck ck KA ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckok 0 4 NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION 46 Special Surveys Division Residential Telephone Service Survey May 2003 User Guide
34. ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck kockok 0 3 NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION Special Surveys Division 53 Residential Telephone Service Survey May 2003 User Guide 11 0 Weighting Since the Residential Telephone Service Survey RTSS used a sub sample of the Labour Force Survey LFS sample the derivation of weights for the survey records is clearly tied to the weighting procedure used for the LFS The LFS weighting procedure is briefly described below 11 1 Weighting Procedures for the Labour Force Survey In the LFS the final weight attached to each record is the product of the following factors the basic weight the cluster sub weight the stabilization weight the balancing factor for non response and the province age sex and sub provincial area ratio adjustment factor Each is described below Basic Weight In a probability sample the sample design itself determines weights which must be used to produce unbiased estimates of the population Each record must be weighted by the inverse of the probability of selecting the person to whom the record refers In the example of a 2 simple random sample this probability would be 0 02 for each person and the records must be weighted by 1 0 02 50 Due to the complex LFS design dwellings in different regions will have different basic weights Because all elig
35. ck ck ck ck ck ck ck ck ck ck ck k KG KOK 142 o NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION Special Surveys Division 45 Residential Telephone Service Survey May 2003 User Guide RESIDENTIAL TELEPHONE SERVICE SURVEY May 2003 Approximate Sampling Variability Tables Ontario NUMERATOR OF ESTIMATED PERCENTAGE PERCENTAGE 000 0 1 1 0 2 0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 70 0 90 0 1 80 3 79 9 795 78 3 7632 74 1 71 9 69 6 67 2 64 8 62 2 56 8 44 0 25 4 2 56 8 56 5 56 2 55 4 53 9 52 4 50 8 49 2 47 5 45 8 44 0 40 2 sd 18 0 3 46 4 46 1 45 9 45 2 44 0 42 8 41 5 40 2 38 8 37 4 35 9 32 8 25 4 14 7 4 40 1 40 0 39 8 39 1 38 37 0 3549 34 8 33 6 32 4 ST 28 4 22 0 12 7 5 ORC HERE 35 7 35 6 35 0 34 33 1 32 4 3144 30 29 0 27 8 25 4 9 7 11 4 6 BARTH 32 6 32 5 32 0 31 30 2 29 3 28 4 27 4 26 4 25 4 23 2 8 0 10 4 7 KERKKERE 30 2 30 1 29 6 28 8 28 0 2d 2 26 3 25 4 24 5 2 9 21 5 6 6 9 6 8 A 28 3 28 1 27 7 26 9 26 2 25 4 24 6 23 8 22 9 22 0 20 1 5 6 9 0 9 Wok ee ot 26 6 26 5 2641 25 4 24 7 24 0 23 2 22 4 21 6 20 7 8 9 4 7 8 5 0 DS RAS UE 25 3 25 24 8 24 23 4 2253 22 0 21 3 20 5 9571 8 0 3 9 8 0 1 FERINA 24 24 0 23 6 23 0 223 els T 21 0 20 3 9 5 8 8 7 1 Sod uad 2 SEE EAE 23 23 0 22 6 22 0 21 4 20 7 20 1 9 4 8 7 8 0 6 4 2 7 NS 3 RAK RRL de 22 2 22d 21 4 21 20 5 9 9 953 8 6 8 0 Tea 5 8 242 7 0 4 AREA Ee 21 4 21 3 20 9 2
36. k k k K 24 ck ck k k k k k k k k K k k k k k k k k k k k k k k k k k k k k K 25 ck k k k k k k k k k k k k k k k k k k k k k k k k k k k k KKK 30 ck k ck k k k k K k K K k k k k K K k K k k k k k k k k k k k k k k k k k k k k K 35 ck ck k k k k k k k k K k k k k k k k k k k k k k k k k k k k k Kk k k k k k AA 40 ck ck k k k k k k k k k k k k k k k k k k k k k k k k k k k k Kk k k I AA 45 50 55 ck ck ck k ck k k KA k K k KKK K K k K K k K x x K K k K K k K K k K k k k k k k k k k k k AA 60 65 70 75 80 85 90 95 100 125 150 200 250 KK RK RK RK kok kok RK kok ck ckck ck ck RARA k kok RK kok k k RK ck ck KK RK ck ckck ck RR ckck ck KK KK KK KKK KKK ck ckck KKK KKK KKK KKK KKK KKK KKK KK KK KKK KEK NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION 44 35 0 NNU v N 300 w O HP M Q Ui O O0 O I9 Ui O HS O0 to Q O1 1 XO ES 4S O uS OO N Q o NOWA uS gt 00 HS ss aS uS dS uS O1 UI UI Q OY Oy 1 N O0 O0 OO OO iO tO XO O O O IP F N N 0 BON o 40 0 50 0 70 0 37 34 26 26 24 18 21 Tos 15s
37. k k k k k k k k K k K K K 8 4 8 2 3 UV 7 4 uu 6 9 6 3 4 9 2 8 40 CKCkckckckckckck ck k ck kckckckck ck k ck k ck kckck ck ck ck ck ckck ck ok WERE evi 7 4 ymo 5 hi 6 7 6 4 5 9 4 6 2 6 45 EZ 7 0 6 8 6 6 6 3 6 545 4 3 2 5 50 6 9 6 6 6 4 6 2 6 0 5 8 SS 4 1 224 55 6 5 6 3 6 1 5 9 BART 555 5 0 3 9 2 2 60 6 3 6 5 9 5 7 5 5 3 4 8 3o d Ze L 65 KKK KKK KKK KKK KKK kok sk KKK KK KKK KKK KKK KKK ck ck ck ck ckckckckck ko ko kk 5 8 5 6 5 5 5 63 D 4 6 3 6 2 1 70 5 6 5 4 5 3 5 1 4 9 4 4 3 4 2 0 75
38. kk kk kk kk kk kk kk ck ck ck KA ck ck ck ck KA ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck k ck ck ki 0 5 NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION Special Surveys Division 51 Residential Telephone Service Survey May 2003 User Guide RESIDENTIAL TELEPHONE SERVICE SURVEY May 2003 Approximate Sampling Variability Tables Prairie Provinces NUMERATOR OF al NNNNN Oy is On o O N Q O XO Q D o oe N CQ Q J O IV Qi O Q NONN ONAN 4S 00 N O O IV O O O1 O1 O gt 0 P N G SEA OY OY O O NNN O0 O0 to io O P P N 0 WWA dS O1 O1 O O Jo o ESTIMATED PERCENTAGE 10 0 56 40 32 28 254 23 21 20 O1 U1 Q OQ OY OY OY OOO P gt N WWW S 0101000 F2 d 00 O M d OY O0 O Q 1 O Ui O O ds Oy OO 4S O ds OO IX I9 O0 4 O o UND 4 AON oo D CKCkckckckckckck ck ck ck kckckckck ck k ck KA KA KA KA k ck KA KA KA ck ck kek aE TKK ROK OK OK ROK k ck k ck KA KA KA KA k k KA KA KA KA ck ck ck ck ck ck ok 15 0 55 39 3T 27 24 22 20 w o Q 4S S UI t Q OY OY OY O O J N J OO OO io O LS p HH N N G 0 2 S 4S 0101000 XO Ul XO O1 O0 O I S Oy OO BRONN Q gt O Q UI OO O 1 O S OO QO OO ww OY Q iS O
39. main types of point estimates of population characteristics which can be generated from the microdata file for the RTSS 9 3 1 Categorical Estimates Categorical estimates are estimates of the number or percentage of the surveyed population possessing certain characteristics or falling into some defined category The number of households which did not have telephone service for their residence during the reference month or the proportion of households which had two or more telephone lines for their residence are examples of such estimates An estimate of the number of persons possessing a certain characteristic may also be referred to as an estimate of an aggregate Examples of Categorical Questions Q How many different telephone numbers are there for your residence 0 1 2 3 or more deductions less or more than LICO R Q In 2002 was your total annual household income before taxes and R Less than more than 9 3 2 Quantitative Estimates Quantitative estimates are estimates of totals or of means medians and other measures of central tendency of quantities based upon some or all of the members of the surveyed population They also specifically involve estimates of the form X Y where X is an estimate of surveyed population quantity total and Y is an estimate of the number of persons in the surveyed population contributing to that total quantity Note that there were no true quantitative questions in the RTSS application Sp
40. monthly Some variables on the sampling frame play a critical role with respect to the software application used in the survey For example in the RTSS computer assisted interviewing CAI application each record must have accurate stratum cluster and rotation group codes These variables are always of very high quality each month in the LFS At times duplication of records occurs This did not happen in May 2003 8 2 2 Data Collection Interviewer training consisted of reading the RTSS Procedures Manual practicing with the RTSS training cases on the laptop computer and discussing any questions with senior interviewers before the start of the survey A description of the background and objectives of the survey was provided as well as a glossary of terms and a set of questions and answers Interviewers collected RTSS information after the LFS information was collected The collection period ran from the 18th to the 24th of May 2003 8 2 3 Data Processing During processing of the data 27 RTSS records did not match to corresponding records in the LFS Thus they were coded as out of scope and were dropped from further processing When supplementary survey records do not match to host survey records they must be dropped since a weight cannot be derived for them Conversely 2 943 records in the LFS were found that should have matched to an RTSS record but did not These records were coded as in scope since they were eligible record
41. of any characteristic for which information is collected by the LFS However these estimates will be based on a frame that contains some information that may be several years out of date and therefore not representative of the current population Through the use of more up to date auxiliary information about the target population the sample weights are adjusted to improve both the precision of the estimates and the sample s representation of the current population Independent estimates are available monthly for various age and sex groups by province These are population projections based on the most recent Census data records of births and deaths and estimates of migration In the final step this auxiliary information is used to transform the sub weight into the final weight This is done using a calibration method This method ensures that the final weights it produces sum to the census projections for the auxiliary variables namely totals for various age sex groups economic regions ER census metropolitan areas CMA rotation groups household and economic family size Weights are also adjusted so that estimates of the previous month s industry and labour status estimates derived from the present month s sample sum up to the corresponding estimates from the previous month s sample This is called composite estimation The entire adjustment is applied using the generalized regression technique This final weight is normally not used in the
42. of the estimate should be determined If this number is less than 30 the weighted estimate should be considered to be of unacceptable quality For weighted estimates based on sample sizes of 30 or more users should determine the coefficient of variation of the estimate and follow the guidelines below These quality level guidelines should be applied to weighted rounded estimates All estimates can be considered releasable However those of marginal or unacceptable quality level must be accompanied by a warning to caution subsequent users Quality Level Guidelines Quality Level of Estimate 1 Acceptable Estimates have a sample size of 30 or more and low coefficients of variation in the range of 0 096 16 596 No warning is required 2 Marginal Estimates have a sample size of 30 or more and high coefficients of variation in the range of 16 696 33 396 Estimates should be flagged with the letter M or some similar identifier They should be accompanied by a warning to caution subsequent users about the high levels of error associated with the estimates 3 Unacceptable Estimates have a sample size of less than 30 or very high coefficients of variation in excess of 33 3 Statistics Canada recommends not to release estimates of unacceptable quality However if the user chooses to do so then estimates should be flagged with the letter U or some similar identifier and the following warning should accompany the esti
43. phone Yes No Refused Don t know Those who answered 0 0 telephone number in RTS Q01B If there were an emergency at home would members of your household have easy access to a payphone near your residence Yes No Refused Don t know Those who answered 0 0 telephone number in RTS Q01B If there were an emergency at home would any member of your household have convenient access to a telephone near your residence at another location not already mentioned 1 2 8 9 Coverage RTS Q08 cO OO N Coverage RTS_I08 Yes No Refused Don t know Those who answered 0 0 telephone number in RTS_Q01B In 2002 was your total annual household income before taxes and deductions less or more than LICO Less than More than Refused Don t know All respondents Thank you for your cooperation Special Surveys Division 61 Residential Telephone Service Survey May 2003 User Guide 13 0 Record Layout with Univariate Frequencies Residential Telephone Service Survey May 2003 Public Use Microdata File Section Demographic Variable Variable Name PROV1 Position 1 Length 2 Province FREQ WTD 10 Newfoundland and Labrador 1 512 197 514 11 Prince Edward Island 1 071 53 866 12 Nova Scotia 2 369 369 873 13 New Brunswick 2 198 292 904 24 Quebec 7 453 3 109 222 35 Ontario 11 625 4 558 427 46 Manitoba 2 903 431 859 47 Saskatchewan 2 979 383 326 48 Alberta 4 085 1 170 038 59 British Columbia
44. the current month In each dwelling information about all household members is usually obtained from one knowledgeable household member Such proxy reporting which accounts for approximately 6596 of the information collected is used to avoid the high cost and extended time requirements that would be involved in repeat visits or calls necessary to obtain information directly from each respondent If during the course of the six months that a dwelling normally remains in the sample an entire household moves out and is replaced by a new household information is obtained about the new household for the remainder of the six month period At the conclusion of the LFS monthly interviews interviewers introduce the supplementary survey if any to be administered to some or all household members that month 6 2 Supervision and Quality Control All LFS interviewers are under the supervision of a staff of senior interviewers who are responsible for ensuring that interviewers are familiar with the concepts and procedures of the LFS and its many supplementary surveys and also for periodically monitoring their interviewers and reviewing their completed documents The senior interviewers are in turn under the supervision of the LFS program managers located in each of the Statistics Canada regional offices 6 3 Non response to the Labour Force Survey Interviewers are instructed to make all reasonable attempts to obtain LFS interviews with membe
45. 0 4 9 8 9 2 8 6 8 0 Tad 6 6 5 2 1 8 6 8 5 AENA 20 6 20 5 20 2 9 71 9 1 8 6 8 0 7 4 651 Sal 4 7 1 4 6 6 6 AS AoA 20 0 9 59 9 6 9 8 5 8 0 7 4 6 8 6 2 S 4 2 1 0 6 4 7 Wok tot 9 4 9 3 9 0 8 5 8 0 7 4 6 9 6 3 5 7 Sal 3 8 0 7 6 2 8 BERATER 8 8 8 7 8 5 8 0 1 9 6 9 6 4 9 8 3 43 4 7 3 4 0 4 6 0 9 AREA REARS 8 3 8 2 8 0 7 5 7 0 6 5 6 0 5 4 4 9 4 3 3 0 0 1 5 8 20 a 7 9 7 8 7 5 7 0 6 6 6 1 5 6 5 0 4 5 349 2471 9 8 5531 21 WO RU Ee 7 4 7 4 Tal 6 6 6 2 Du 5 2 4 7 4 1 3 6 2 4 9 6 5 5 22 Wh ER 7 0 7 0 6 7 6 2 3 68 9 3 4 8 4 3 3 8 3 53 Ziel 9 4 5 4 23 KARA ORO 651 6 6 6 3 5 9 5 4 5 0 4 5 4 0 3 8 3 0 1 8 9 2 Did 24 IA 6 3 6 2 6 0 5 6 Sul 4 7 4 2 3 7 342 2 7 1 6 9 0 9 2 25 Wok eoo 6 0 549 5 7 9 82 4 8 4 4 3 9 3 4 3 0 2 4 1 4 8 8 5 1 30 4 6 4 5 4 3 349 3 5 3 1 CARS 2 3 1 8 1 4 0 4 8 0 4 6 35 BREA REARS 925 3 4 Su2 2 9 2 5 Zel Tog 1 4 0 9 0 5 9 6 7 4 4 3 40 EA 2 6 2 6 2 4 240 Tu 1 4 1 0 0 6 0 2 9 8 9 0 7 0 4 0 45 EAS 9 1 9 1 7 1 4 1 0 0 7 0 4 0 0 91 9 3 8 5 6 6 3 8 50 BEKELE EAN aee Tez 1 51 0 8 0 5 0 2 9 8 9 8 952 8 8 8 0 6 2 3 6 55 SIERT JO FERNE 0 7 0 6 0 3 0 0 gt 9 4 9 1 8 7 8 4 7 7 5 9 3 4 60 ARENA Ko a poe 0 3 Od 9 8 9 6 9 3 9 0 8 7 8 4 8 0 7 3 Dis I 65 a kp aio a e 9 9 Ou 945 9 2 8 9 8 6 8 3 8 0 ERST 7 0 39 3 2 70 PRA AS BRIA oie 9 5 9 4 9 1 8 9 8 6 Bod 8 0 Tegel 7 4 6 8 5423 3 0 45 EIER x KK OE ot ce 9 2 9 0 8 8 8 6 8 3 8 0 7 8 dao 7 2 6 6 Sal 2 9 80 OR OK ORE NR E e Rok KK 8 9 8 8 85 8 3 8 0 7 8 Ju 7 2 7 0 6 4 4 9 2 8 85 a BLAS AAS SE 8 6 8 5
46. 02 2 or RTS Q03 2 Variable Name Q05 Position 16 Length 1 If there were an emergency at home would members of your household have easy access to a neighbour s phone FREQ WTD 1 Yes 491 126 501 2 No 70 24 101 6 Valid skip 39 337 12 035 196 7 Don t know 12 2 602 8 Refused 6 732 9 Not stated 8 2 173 39 924 12 191 305 Coverage Those who answered 0 0 telephone number in RTS_Q01B Special Surveys Division 69 Residential Telephone Service Survey May 2003 User Guide Residential Telephone Service Survey May 2003 Public Use Microdata File Variable Name Q06 Position 17 Length 1 If there were an emergency at home would members of your household have easy access to a payphone near your residence FREQ WTD 1 Yes 317 94 005 2 No 238 54 862 6 Valid skip 39 337 12 035 196 7 Don t know 17 3 870 8 Refused 6 732 9 Not stated 9 2 639 39 924 12 191 305 Coverage Those who answered 0 0 telephone number in RTS Q01B Variable Name Q07 Position 18 Length 1 If there were an emergency at home would any member of your household have convenient access to a telephone near your residence at another location not already mentioned FREQ WTD 1 Yes 315 89 788 2 No 240 59 168 6 Valid skip 39 337 12 035 196 7 Don t know 14 2 963 8 Refused 8 1 234 9 Not stated 10 2 956 39 924 12 191 305 Coverage Those who answered 0 0 telephone number in RTS Q01B Variable Name Q08 Position 19 Length 1 In 2002
47. 10 0 9 1 8 7 7 9 6 1 3 5 55 voy 10 6 10 6 10 4 10 2 9 9 9 6 8 6 8 3 7 6 5 9 3 4 60 teet 10 2 10 1 10 0 9 7 9 4 9 2 8 3 7 9 7 2 5 6 3 2 65 ues 9 8 9 7 9 6 9 3 9 1 8 8 7 9 7 6 7 0 5 4 3 1 LO HERE 9 4 9 4 9 2 9 0 8 7 8 5 7 6 7 3 6 7 5 2 3 0 15 ERES 9 1 9 1 8 9 8 7 8 5 8 2 7 4 7 1 6 5 5 0 2 9 80 8 8 8 8 8 6 8 4 8 2 7 9 7 2 6 9 6 3 4 9 2 8 85 er 8 6 8 5 8 4 8 2 7 9 7 7 6 9 6 7 6 1 4 7 2 7 90 trees 8 3 8 3 8 2 7 9 7 7 75 6 7 6 5 5 9 4 6 2 6 95 eee 8 1 8 1 7 9 7 7 75 7 3 6 6 6 3 5 8 4 5 2 6 LON 7 9 7 9 7 7 ES DES Tal 6 4 6 1 5 6 4 3 2 5 125 5 pue cou 7 0 6 9 6 7 6 5 6 4 5 7 5 5 5 0 3 9 2 2 150 mo cem 6 4 6 3 6 1 6 0 5 8 5 2 5 0 4 6 3 5 2 0 20059 9259 5 6 5 5 5 8 5 2 5 0 4 5 4 3 4 0 3 1 1 8 250 rn AAA ARA 4 9 4 8 4 6 4 5 4 0 3 9 3 5 2 7 1 6 300 eee ee A 4 5 4 3 4 2 4 1 3 7 3 5 3 2 25 1 4 ii E AET ENE 4 1 4 0 3 9 3 8 3 4 3 3 3 0 2 3 1 3 400 Fre ge a RES 3 9 3 8 3 7 3 5 3 2 3 1 2 8 2 2 1 3 450 AEREAS ES 3 6 3 5 3 4 3 3 3 0 2 9 2 6 2 0 1 2 5002 Se SE Wann 3 5 3 4 3 3 3 2 2 9 2 7 25 1 9 1 1 8000 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkk k kkkkkkkk ck ke e 0 5 0 3 9000 KKKKKKKK kkkkkkkk kkkkkkkk ck ek e e kkkkkkkk ck ee e e x KKKKKKKK kkkkkkkk 0 3 10000 kkkkkkkk kkkkkkkk kkkkkkkk
48. 2 Residential Telephone Service Survey May 2003 User Guide non sampling errors in the survey Quality assurance measures were implemented at each step of the data collection and processing cycle to monitor the quality of the data These measures include the use of highly skilled interviewers extensive training of interviewers with respect to the survey procedures and questionnaire observation of interviewers to detect problems of questionnaire design or misunderstanding of instructions procedures to ensure that data capture errors were minimized and coding and edit quality checks to verify the processing logic 8 2 1 The Frame Because the Residential Telephone Service Survey was a supplement to the LFS the frame used was the LFS frame Any non response to the LFS had an impact on the RTSS frame Because non response to the LFS is quite low usually less than 5 this impact was minimal The quality of the sampling variables in the frame was very high The RTSS sample consisted of five rotation groups from the LFS No records were dropped due to missing rotation group number or any other type of sampling variable Note that the LFS frame excludes about 2 of all households in the 10 provinces of Canada Therefore the RTSS frame also excludes the same proportion of households in the same geographical area It is unlikely that this exclusion introduces any significant bias into the survey data All variables in the LFS frame are updated
49. 5 ARA 32 6 32 4 31 9 3 30 2 29 3 28 4 27 4 26 4 25 4 23 2 19 10 4 6 TREUEN 29 8 29 6 29 1 28 4 27 6 26 7 25 9 25 0 24 1 23 2 214 6 4 7 EXAHANEAE 27 5 27 4 27 0 26 3 25 5 24 8 24 0 23 2 22 3 21 4 9 6 5 2 8 8 8 FERRERA 25 8 25 6 25 2 24 6 23 9 23 2 22 4 21 7 20 9 20 8 3 4 2 8 2 9 ARTE GAR 24 3 24 2 23 8 23 2 22 5 21 8 21 20 4 gt 8 9 Tea 3 4 7 7 0 BEREBER 23 0 22 9 22 6 22 0 21 4 20 7 20 9 4 8 7 74 9 6 4 2u7 t 1 AOEEOON EN 22 0 21 9 21 5 21 0 20 4 9 8 9 8 5 8 7 51 6 2 7 0 2 E NU UK Ue 20 9 20 6 20 1 95 5 8 9 8 3 Tau 7 0 6 4 5 0 1 6 6 7 3 DON RRM QS adn donee 20 1 978 913 8 7 8 2 1 6 7 0 6 4 Su 4 4 T 6 4 4 RA A kap ESEE 9 4 9 1 8 6 8 0 f 7 0 6 4 5 8 D 2 3 8 0 7 6 2 5 Ckckckckckckckckckckck KK KKK 8 7 8 4 7 9 7 4 6 9 6 4 5 8 5 2 4 7 3 4 0 4 6 0 6 FERRER RAE SAREE KE 8 1 7 8 7 4 6 9 6 4 559 543 4 8 4 2 2 49 0 0 5 8 7 O Sad 7 6 T3 6 49 6 4 59 5 4 4 9 4 3 3 8 2 6 gt R 5 6 8 EN RAR LEE PANA Se T 1 6 8 6 4 549 5 4 3 40 4 4 3 9 3 4 22 955 5 5 9 A RAE OA SEGK OUR 6 6 6 4 5 9 5415 5 0 4 6 4 3 25 3 0 14 9 9 2 533 20 RAS Eu 6 2 6 0 545 Du 4 7 4 2 347 34 2 2 7 1 6 9 0 5 2 21 MERGE Ken a e ope o KR 5 8 5 6 5 2 4 7 4 3 3 8 3 4 2 9 2 4 123 8 8 S l 2 AE IS GERE OE A UE 555 9 2 4 8 4 4 4 0 33 9 3 26 2 1 1 9 8 6 4 9 23 SARA AE RAR EEEE 5l 4 9 4 5 4 Suh 3 2 2 8 2 3 1 49 0 8 8 4 4 8 24 FAN LACE IEA KK Roo e 4 6 4 2 3 8 3 4 239 245 2 1 1 6 0 6 8 2 4 7 25 i Koo KR pk mole c cce 4 3 3 9 Sub 341 241 2 3 14 8 1 3 0 4 8 0 4 6 30 EN SS RAN TRUE 3 0
50. 8 3 8 0 7 8 12 7 3 7 0 6 7 6 2 4 8 2 8 90 kas u khi NARA 8 4 8 3 8 0 7 8 7 6 qu 7 1 6 8 6 6 6 0 4 6 2 95 SEO KO ee ake a A 8 0 7 8 7 6 7 4 7 1 6 9 6 6 6 4 5 8 4 5 2 6 100 7 8 7 6 Fi 9 7 0 6 7 6 5 6 2 Z 4 4 2D 125 6 8 6 6 6 4 6 2 6 0 5 8 5 6 521 3 9 243 150 JI KOCKOCKUE WOK ORIG KOKRCRCKOKU OR 6 4 6 2 6 0 5 9 Sl 5 5 5 3 Sol 4 6 S36 2v 200 SEE OK KON IGEA KON KO A icio KK oves 55 5 5 4 5 2 5 4 9 4 8 4 6 4 4 4 0 Ju 1 8 250 Ok Ck Ck kk kk kk KK KK KK KK KK KK ck ck ck ck ckck ck ck kk ok 4 8 4 7 4 5 4 4 4 3 4 1 3 9 3 6 2 8 1 6 300 Ok Ck Ck kk kk kk kk kk kk KA KK KK ck ck ck ck ck ck ckck kk ck 4 4 4 3 4 4 0 3 9 37 3 6 3553 2 5 1 5 350 4 1 4 0 38 3 3 6 3 5 3 3 3 0 2 4 1 4 400 Ok Ck Ck kk kk kk kk KK KK KK KK KK KK ck ck ck ck KK kk ok 3 8 3 7 3 6 3 5 3 4 3 9 Fi 2 8 2 2 1 3 450 3 6 S Ei Bud 3 3 Sud 3 1 2 9 25 273 142 500 Ok kk kk kk kk kk KK KK ck kk ck KA KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK 3 3 SUN SAL 3 0 2 9 2 8 2 5 2 0 eri 750 Ok kk KKK KKK KK KK KK KK KK KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck
51. 9 135 1 791 468 39 924 12 191 305 Special Surveys Division 71 Residential Telephone Service Survey May 2003 User Guide Residential Telephone Service Survey May 2003 Public Use Microdata File Survey Date Variable Section Variable Name SDATE Position 32 Length Survey date YYYYMM FREQ 200305 200305 39 924 39 924 WTD 12 191 305 12 191 305 72 Special Surveys Division
52. E PERCENTAGE 000 0 1 1 0 2 0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 70 0 90 0 T eS OR EG 47 3 47 0 46 3 45 1 43 8 42 5 41 2 39 8 38 3 36 8 33 6 26 0 15 0 2 AER 33 4 33 3 32 7 31 9 31 0 30 1 29 1 28 1 27 1 26 0 23 8 18 4 10 6 3 ERRADA 251 53 214 2 26 7 26 0 25 3 24 5 23 8 23 0 221 21 3 19 4 15 0 8 7 4 SARE RAE 23 6 23 5 23 2 22 5 21 9 21 3 20 6 9 9 952 8 4 16 8 13 0 T S 5 ARA 2141 21 0 20 7 20 2 9 6 9 0 8 4 7 8 ASA 6 5 15 0 11 6 6 7 6 de 194 3 9 2 8 9 8 4 34 9 7 4 6 8 6 2 54 6 5 0 13 7 10 6 6 1 7 RARE NE A VESI 18 qd 7 0 6 6 6 1 5 6 5 0 4 5 3 9 12 57 9 8 5 7 8 FAA SAE 16 7 6 6 6 4 5 9 5 5 5 0 4 5 4 1 34 5 3 0 11 9 952 5 3 9 A RATE 15 8 Dis i 5 4 530 4 6 4 2 3 7 93 2 8 2 3 11 2 gu 50 0 BERNER 4 9 4 6 4 3 3 9 3 4 3 0 2 6 Za L 1 6 10 6 8 2 4 8 1 RE EA AEE RR Poe NAT 4 2 4 0 3 6 3 2 2 8 2 4 2 0 1 6 Ts 109 1 7 8 4 5 2 SAAN SAE LAR PRE 3 6 3 4 3 0 2 6 243 1 9 1 5 1 1 0 6 95 7 7 5 4 3 3 to e e ade nS e oko 3 0 2 8 245 2 2 1 8 1 4 1 0 0 6 0 2 9 3 7 2 4 2 4 ERAS A 236 2 4 230 1 47 1 4 17 0 0 6 0 2 9 8 9 0 120 4 0 9 RAR AIA ERASE AE kuk 21 2 0 1536 1 3 1 0 0 6 0 3 9 9 9 5 gv 6 7 3 9 6 EAA RAE S 235 1 8 1 6 143 140 0 6 0 3 9 9 93 6 9 2 8 4 6 0 3 8 7 AR EUR E 1 4 1 2 0 9 0 6 0 3 0 0 9 6 9 3 8 9 gd 623 3 6 8 BS RENAL PARA LL 0 9 0 6 0 3 0 0 9 7 9 4 9 0 8 7 y 9 6 1 3 5 9 PEER RAE BASE IR SUE OR KO Si 0 6 0 3 0 1 9 8 9 4 9 1 8 8 8 4 TEST 6 0 3 4 20 EFRERFRACAT READER RARA 0 4 0 1 9 8 945 942 8 9 8 6 8 2 Ts 5 8 3 4 21 A St
53. ENTATION RESIDENTIAL TELEPHONE SERVICE SURVEY NOVEMBER 2002 Approximate Sampling Variability Tables Ontario NUMERATOR OF ESTIMATED PERCENTAGE PERCENTAGE 000 0 1 1 0 2 0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 70 0 90 0 1 105 6 105 1 104 6 103 0 100 2 97 4 94 5 91 5 88 4 85 2 81 8 74 7 57 9 33 4 2 74 7 74 3 74 0 72 8 70 9 68 9 66 8 64 7 62 5 60 2 57 9 52 8 40 9 23 6 3 61 0 60 7 60 4 59 5 57 9 56 2 54 6 52 8 51 0 49 2 47 2 43 1 33 4 19 3 250 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk 6 3 6 2 6 0 5 8 5 6 5 4 5 2 4 7 3 7 2 1 a 58 56 55 53 51 49 47 43 33 19 350 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk 5 4 5 2 5 1 4 9 4 7 4 6 4 4 4 0 3 1 1 8 400 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk 5 0 4 9 4 7 4 6 4 4 4 3 4 1 3 7 2 9 1 7 A50 RR RR RR kk 47 46 45 43 42 40 39 35 27 16 500 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk 4 4 4 2 4 1 4 0 3 8 3 7 3 3 26 1 5 750 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk 3 5 3 3 3 2 3 1 3 0 2 7 2 1 1 2 OO 29 28 27 26 24 18 14 1500 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk 22 2 1 1 9 1 5 0 9 2000 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk 1 7 1 3 0 7 a 14 0 6 4000 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk 0 5 NOTE FOR CORRECT
54. K ROK RK ck RARA RAR ck ckck ck ck RARA ckck ck ck ckck ck ck ck ck ckck ck ck ck ck ckck ck ck ck RK KK RK RK KK KK KK KK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK hk kok KEK NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION 52 40 0 50 0 70 0 46 42 32 32 29 23 26 24 18 23 21 16 20 8 14 8 13 PRR oon n o N Ui XO S iO OY dS dS gt O N P2 N Q Ui O Q OO OY O0 tO O I 4S UI OO O G OY XO wo QI Q UI tO dS OY XO Q OY O ds o dS O 1 Ui 4S Gn io NOOA O O P Q 4 J O Ui I9 Q O1 O J O QQ t J O Q J I UI O O O I UN O Q GO XO Q IO O0 gt O O G i0 N G o dS N S N G Q 4S S aS dS O1 UI UI UI OU OY O ON ON J OO Oo o XO t0 O O O O P BF N N N Q0 S BUD A P2 N N N N 2 4S uS ds dS aS uS UI Q UI Q OA OY OY OO CO OO O tO tO i0 O O O O P F N N QG BRUON m m a pj op p p p p p 2 IO Q Q Q 0 Q QQ 0 dis uS uS uS S O1 Qn OY OY O O 1 NN O O M UO Ui O OO O 0 tO Q RUAN OO OH S i gt Oy XO NN G O G O O I Q UI J O IN Gn 0o Special Surveys Division 90 0 PRR OW SGOCODOOKRPKFPHPHEEHEEHEEHENYNNNNNNNNNWWWWWWE gt 5 ERR gt E G Q Q Q O O O OO Qn OY O0 tO tio O I9 Q G to 0 O HP P N 4S Oy 1 00 O IV Ui O 1o to O gt N WAAN o gt Q O1 H O QG I G G Qo BW Residential Telephone Service Survey May 2003
55. KA KA KARA OR S kok kok KA KA KA KA kuk KA KA ck kok RT CKCkckckckck ck k ck ck ck k ck k ck k ck k ck k ck k ck k ck kckck ck kckckckckckckckck ck kckckckckckckckckckckckck ck k ck ck ck ck ck ck ck AA 30 0 40 3 28 5 23 2 20 8 0 6 4 5 2 4 2 3d 2 7 1 6 1 2 0 8 0 4 0 9 8 94 5 922 9 0 8 8 8 6 8 4 8 2 8 1 1 43 6 8 6 4 6 0 Set 5 4 542 5 0 4 8 4 6 4 5 4 4 CKCkckckckck ck k ck k ck k ck k ck k kok k ck k ck k ck kckckckck ck k ck kckckckck ck kckckckckckckckckckckckckckckckckckckckckckck ck kckck ck ck ck ck ck ok CKCkckckckck ck kckck ck k ck k ck k ck k ck k ck kckck ck k ck kckck ck kckckckckckckckckckckckckckckckckckckckckckckckckckckckckck ck ckckckck ck ck ckck ck ck CKCkckckckckckck RARA ck kckckckck ck k ck k ck k ck k ck k ck k ck kckckckckckckckckckckckckckckckckckckckckckckckckckckckckckck ck ck ck ck ck ck ckckckok CKCkckckckckckck ck ck ckckckck ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck kckck ck kckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckck ck ck ckck ck k CKCkckckckck ck k ck k ck kckck ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck kckckckckckckckck ck kckckckck ck kckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckck ck ck ckck ck ck CKCkckckckck ck ck RARA ck k ck kckck ck k ck k ck k ck k ck k ck k ck k ck k ck kckck ck kckckckck ck kckck ck k ck kckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckc
56. Measures from 1991 to 2000 Catalogue no 75F0002MIE for the full definition of LICO For the purpose of the Residential Telephone Service Survey RTSS the low income values used to assess the level of income were rounded to the nearest 500 The total income was collected for the entire household regardless of family structure LICOs normally apply to economic families and unattached individuals Respondents were asked to self report if their total household income was above or below the modified LICO with no additional prompting for precision Although Statistics Canada s LICOs are often referred to as poverty lines they do not have an officially recognized status nor does Statistics Canada promote their use as poverty lines Since the LICOs are recognized Statistics Canada income measures and as modifications were made to them for the purpose of the RTSS we recommend that the term LICO not be used to refer to the RTSS income measure as this could be misleading to unadvised readers Special Surveys Division 11 Residential Telephone Service Survey May 2003 User Guide 5 0 Survey Methodology The Residential Telephone Service Survey RTSS was administered in May 2003 to a sub sample of the dwellings in the Labour Force Survey LFS sample and therefore its sample design is closely tied to that of the LFS The LFS design is briefly described in Sections 5 1 to 5 4 Sections 5 5 and 5 6 describe how the Residential Telephone Service S
57. Microdata User Guide RESIDENTIAL TELEPHONE SERVICE SURVEY May 2003 ee La Pel Eus mun Canada Residential Telephone Service Survey May 2003 User Guide Table of Contents 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 Introduction A recede ec e atas 5 Background est 7 G bjectives ou a a aa Er aaa aa a aaa aa aaa eA a aae aeaa aeaa e Eae raaa 9 Concepts and Definitions uuu 0 el 11 Survey Methodology u apetece raa es Ri 13 5 1 Population COVerag8 2 uu ee ei ayapa kuwa 13 5 2 Sample Design iiie Ies ei died and eni un led Fate heee 13 5 2 1 Primary Stratificatigm a 13 5 2 2 TIPOS OR ATGaS ir u uuu a iaa 13 5 2 3 Secondary Stratification 0 14 5 2 4 Cluster Delineation and Selection 14 5 2 5 Dwelling Selection pp 15 5 2 6 P rson Selectionz eicit unap q lanes er e fede dea Lee AERE de ha 15 5 3 Sample Silicio ita 15 5 4 Sample Rotation u u a rad er 15 5 5 Modifications to the Labour Force Survey Design for the Residential Telephone SEIVICE SUIVOV a a lb a ed a oa laa 16 5 6 Sample Size by Province for the Residential Telephone Service Survey 16 Data Collection Ete E 17 6 1 Interviewing for the Labour Force SUrVey pp 17 6 2 Supervision and Quality Control nennen nennen 17 6 3 Non response to the Labour Force Survey Nt 17 6 4 Data Collection Modifications for the Residential Teleph
58. Not stated 24 5 835 39 924 12 191 305 Coverage Respondents who cannot afford a phone RTS_Q02 2 or RTS Q03 2 66 Special Surveys Division Residential Telephone Service Survey May 2003 User Guide Residential Telephone Service Survey May 2003 Public Use Microdata File Variable Name Q042 Position 10 Length am going to read a list of most common charges which could be on a telephone bill Please tell me which of these charges you find difficult to afford The security deposit FREQ WTD 2 Yes 201 49 890 6 Valid skip 39 688 12 132 510 7 Don t know 8 2 597 8 Refused 3 473 9 Not stated 24 5 835 39 924 12 191 305 Coverage Respondents who cannot afford a phone RTS_Q02 2 or RTS Q03 2 Variable Name Q043 Position 11 Length 1 am going to read a list of most common charges which could be on a telephone bill Please tell me which of these charges you find difficult to afford Monthly charge for your basic phone line which includes local calls FREQ WTD 3 Yes 258 67 680 6 Valid skip 39 631 12 114 720 7 Don t know 8 2 597 8 Refused 3 473 9 Not stated 24 5 835 39 924 12 191 305 Coverage Respondents who cannot afford a phone RTS_Q02 2 or RTS Q03 2 Special Surveys Division 67 Residential Telephone Service Survey May 2003 User Guide Residential Telephone Service Survey May 2003 Public Use Microdata File Variable Name Q044 Position 12 Length 1 am going to read a list of most common cha
59. O OO O O1 Q IS Coverage 60 Residential Telephone Service Survey May 2003 User Guide Why don t you have a phone Canceled ll mat bt tae te Go to RTS_Q03 Gan atordita msc en tia ea eaten Go to RTS Q04 MOV TEIL Go to RTS Q05 All other responses nn Go to RTS Q05 REUS IR Go to RTS Q05 DONE Westin tace rerit bere pate Terba n Porra avus bipes manda hehe ren Go to RTS Q05 F1 NOTES The following answers should be coded to Can t afford it Too expensive Can t afford the phone Unpaid phone bills Service cancelled by the phone company Moved and can t afford the installation price Lost job Unemployed I m on any form of social assistance etc The following answers should be coded to Moved Respondent moved on vacation going south for the winter moved and don t want need the phone anymore etc The following answers should be coded to Any other response Sharing a phone receiving harassing calls getting a private number hard of hearing dissatisfied with the phone company don t want other household members to receive calls etc Respondents who do not have phones RTS Q01B 0 Why did you cancel it Can t afford it Moved uat tat i n Go to RTS Q05 All other responses nn Go to RTS Q05 REUS A Go to RTS Q05 Dont KNOW een einen A Go to RTS Q05 F1 NOTES The following answers should be coded to Can t afford it Too expensive Can t afford the phone Unpaid phone bills Service cancel
60. OVEMBER 2002 Approximate Sampling Variability Tables Quebec ESTIMATED PERCENTAGE PERCENTAGE 000 0 196 1 0 2 0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 70 0 90 0 1 88 9 88 5 88 1 86 7 84 4 82 0 79 6 77 0 74 4 71 7 68 9 62 9 48 7 28 1 2 62 9 62 6 62 3 61 3 59 7 58 0 56 3 54 5 52 6 50 7 48 7 44 5 34 5 19 9 3 51 3 51 1 50 8 50 1 48 7 47 4 45 9 44 5 43 0 41 4 39 8 36 3 28 1 16 2 ias 44 3 44 0 43 4 42 2 41 0 39 8 38 5 37 2 35 9 34 5 31 5 24 4 14 1 D TENUES 39 6 39 4 38 8 37 7 36 7 35 6 34 5 33 3 32 1 30 8 28 1 21 8 12 6 NE 6 0 58 56 5 4 53 51 49 44 34 20 250 kkkkkkkk kkkkkkkk kkkkkkkk 5 3 5 2 5 0 4 9 4 7 4 5 4 4 4 0 3 1 1 8 300 kkkkkkkk kkkkkkkk kkkkkkkk 4 9 4 7 4 6 4 4 4 3 4 1 4 0 3 6 2 8 1 6 350 Are RR AR o 44 43 41 40 38 37 34 26 15 400 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk 4 1 4 0 3 9 3 7 3 6 3 4 3 1 24 1 4 450 RR een RR RR o 39 38 36 35 34 32 30 23 13 EM 3 6 34 33 32 31 28 22 13 750 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk 2 8 27 26 25 2 3 1 8 1 0 OO 23 22 20 15 0 9 1500 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk 1 6 1 3 0 7 2000 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk 1 0 6 NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUM
61. RRR ckck kk ok 6 4 6 3 6 1 5 9 5 7 5 5 5 3 4 8 3 7 2T 250 Ok Ck Ck kk kk k k kk kk KK KK KK ck ck ck ck ck ck ck ck ck ck Kok k 5 8 5 6 5 4 5 3 5 1 4 9 4 7 4 3 3 3 1 9 300 Ok Ck Ck kk kk kk kk kk kk KA KK KK KK ck ck ck ck kk KK ck 5 3 5 1 5 0 4 8 4 6 4 5 2 3 3 9 3 0 1 8 350 KKK KK KKK KKK KK KK KK KK KK KK KK RK RK KKK KKK 4 7 4 6 4 4 4 3 4 1 4 0 3 6 2 8 1 6 400 Ok kk kk kk kk KK KK kk ck kk ck KK KK ck ck ck ck ck ck ck ck ck ck ck ck ck KK KK 4 4 4 3 4 2 4 0 3 9 3 7 3 4 2 6 1 5 450 Ok Ck kk kk kk kk kk kk kk ck KK KK KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK 4 2 4 0 3 9 3 8 3 6 3 5 3 2 2 5 1 4 500 Ok kk kk kk ok kk kk kk kk ck ck kk kk Ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK 3 8 Qr 3 6 3 5 3 3 3 0 98 3 1 4 750 Ok kk kk kk kk kk a a KK kk KK KK KA KK RK RRR RR RR EE 3 0 2 9 2 8 2 7 2 5 1 9 Pl 1000 Ok kk kk kk ok kk kk kk kk kk kk ck KK KK KK KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckok 2 4 21 2 1 7 1 0 1500 Ok kk kk kk kk kk kk kk kk kk ck kk ck ck ck ck ck KA ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KOK 1 8 T4 0 8 2000 Ok kk kk kk Sk kk kk kk kk kk RR kk KA KA KA ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck
62. Special Surveys Division 49 NUMERATOR OF Residential Telephone Service Survey May 2003 User Guide RESIDENTIAL TELEPHONE SERVICE SURVEY May 2003 Approximate Sampling Variability Tables British Columbia ESTIMATED PERCENTAGE PERCENTAGE 000 0 1 1 0 2 0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 T 79459 7955 7953 77 9 75458 13 7 73 5 69 2 66 9 64 4 61 9 56 5 2 nd 56 2 55 9 54d 53 6 32 1 50 6 48 9 47 3 45 6 43 8 40 0 3 E ERA 45 9 45 7 45 0 43 8 42 5 41 3 40 0 38 6 37 2 3545 3246 4 SRE RAE 39 8 39 6 39 0 37 9 36 8 35 7 34 6 33 4 32 2 31 0 28 3 5 KERERE EE 35 6 35 4 34 8 33 29 33 0 32 0 31 0 29 9 28 8 2 1 25 3 6 E ARA 3255 32 3 31 8 31 0 30 1 29 2 28 3 2763 26 3 253 23 1 7 RAR ANS AE 3071 29 9 29 4 28 7 27 9 27 0 26 2 25 3 24 4 23 4 21 4 8 FAA SAL 28 1 28 0 27 9 26 8 26 1 29 3 24 5 23 6 22 8 21 9 20 0 9 ARE TER UA 26 5 26 4 26 0 2553 24 6 23 8 23 1 22 3 21 5 20 6 8 8 0 AER es 25 0 24 6 24 0 23 3 22 6 21 9 21 1 20 4 9 6 73 9 1 AREER LEAS 24 0 23 9 23 5 22 9 22 2 21 56 20 9 20 2 9 4 8 7 7 0 2 FERRERA 23 0 22 8 22 5 21 9 21 3 20 6 20 0 93 3 8 6 71 9 6 3 3 RAR TE 22 1 21 9 21 6 21 0 20 4 9 8 9 2 8 5 Fed 7 2 Dual 4 WE PEETER 214 3 21 1 20 8 20 3 9 7 9 1 8 5 129 3 2 6 5 Ds L 9 RRA ASE 20 5 20 4 20 1 9 6 9 0 8 5 7 9 7 3 6 6 6 0 4 6 6 EAA A 19 9 9 8 955 9 0 8 4 Tad 743 6 7 6 1 555 4 1 7 nt pt E E 9 2 8 9 8 4 7 9 T3 6 8 6 2 5 6 5 0 Suy 8 8 6 8 4 34 9 7 4 6 9 6 53 5 8
63. Tabulation of Quantitative Estimates 27 9 4 Guidelines for Statistical Analysis sess enne 28 9 5 Coefficient of Variation Release Guidelines pp 28 9 6 Release Cut off s for the Residential Telephone Service Survey 30 Approximate Sampling Variability Tables sienne eene 31 10 1 How to Use the Coefficient of Variation Tables for Categorical Estimates 32 10 1 1 Examples of Using the Coefficient of Variation Tables for Categorical ESMAS iuste ettet deerit eio o det uite eee spada 33 10 2 How to Use the Coefficient of Variation Tables to Obtain Confidence Limits 38 10 2 1 Example of Using the Coefficient of Variation Tables to Obtain Confidence ElmitS dr M 39 10 3 Howto Use the Coefficient of Variation Tables to Do a T test 39 10 3 1 Example of Using the Coefficient of Variation Tables to Do a T test 40 10 4 Coefficients of Variation for Quantitative Estimates pp 40 10 5 Coefficient of Variation Tables nn ncnnnn nn anneta nn enne nnns 41 Weighting sm AnaL AE KARNE EENAA ANENE LAEE An VARER PRAEAN nE RENAA NANAK a Eti 55 11 1 Weighting Procedures for the Labour Force Survey pp 55 11 2 Weighting Procedures for the Residential Telephone Service Survey 56 Questionnaires om ra a e aa e a a raa aa aaa aSa a
64. User Guide RESIDENTIAL TELEPHONE SERVICE SURVEY May 2003 Approximate Sampling Variability Tables Canada NUMERATOR OF ESTIMATED PERCENTAGE PERCENTAGE 000 0 1 1 0 2 0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 70 0 90 0 1 80 5 80 1 79 7 78 5 76 4 74 2 72 0 69 7 67 4 64 9 62 4 56 9 44 1 25 5 2 56 9 56 6 56 4 25 5 54 0 2245 50 9 49 3 47 6 45 9 44 1 40 3 31 2 18 0 3 46 5 46 3 46 0 45 3 44 1 42 9 41 6 40 3 38 9 315 36 0 3209 2545 14 7 4 40 2 40 1 39 9 39 2 38 2 ST 36 0 34 9 33 32 5 31 2 28 5 22 1 12 7 5 36 0 35 8 35 6 35 1 34 2 33 2 32 2 31 2 30 1 29 0 27 9 2555 gt P 11 4 6 32 9 32 7 32 5 32 0 3132 30 3 29 4 28 5 27 5 26 5 255 23 2 8 0 10 4 7 30 4 30 3 30 1 29 7 28 9 28 1 2 42 26 4 25 5 24 5 23 6 21495 6 7 9 6 8 28 5 28 3 28 2 27 7 27 0 26 2 2545 24 7 23 8 23 0 22 1 20 1 5 6 9 0 9 26 8 26 7 26 6 26 2 25 5 24 7 24 0 2952 22 5 21 6 20 8 9 0 4 7 8 5 0 25 4 25 3 25 2 24 8 24 2 23955 22 8 22 21 33 20 5 947 8 0 3 9 8 1 1 24 3 24 2 24 0 293 23 0 22 4 BLET 21 0 20 3 936 8 8 7 2 Sod ad 2 23 2 23 23 0 2247 22 1 21 4 20 8 20 9 4 8 7 8 0 6 4 2 7 7 4 3 RAK ERE 22 2 2241 21 8 21 2 20 6 20 0 953 8 7 8 0 7 3 5 8 2422 7 1 4 WR uibus ue 21 4 21 3 21 0 20 4 9 8 9 2 8 6 8 0 Tid 6 7 5 2 1 8 6 8 5 BRK ARES 20 7 20 6 20 3 Deck 972 8 6 8 0 7 4 6 8 6 1 4 7 1 4 6 6 6 AS X 20 0 9 79 9 6 9a 8 6 8 0 7 4 6 8 6 2 94 6 4 2 1 0 6 4 7 docuit ot 9 4 9 3 9 0 8 5 8 0 dum 6 9 6 3
65. a a Aea maaa aaa maiaa a aa aaa saa Eanna 59 12 1 The Labour Force Survey Questionnaire ssssssssss eene 59 12 2 The Residential Telephone Service Survey Questionnaire 59 Record Layout with Univariate Frequencies J J T 63 Special Surveys Division Residential Telephone Service Survey May 2003 User Guide 1 0 Introduction The latest Residential Telephone Service Survey RTSS was conducted by Statistics Canada in May 2003 with the cooperation and support of Bell Canada This manual has been produced to facilitate the manipulation of the microdata file of the survey results Any questions about the data set or its use should be directed to Statistics Canada Client Services Special Surveys Division Telephone 613 951 3321 or call toll free 1 800 461 9050 Fax 613 951 4527 Email ssd statcan ca Edward Praught Special Surveys Division Room 2500 Main Building Tunney s Pasture Ottawa Ontario K1A 0T6 Telephone 613 951 5386 Fax 613 951 0562 Email ed praught statcan ca Bell Canada Lynn Solvason Regulatory Matters 105 H tel de Ville Street 5 Floor Hull Quebec J8X 4H7 Telephone 819 773 5582 Fax 819 773 5579 Email lynn solvasonObell ca Special Surveys Division 5 Residential Telephone Service Survey May 2003 User Guide 2 0 Background Bell Cana
66. age or older Respondent burden is minimized for the elderly age 70 and over by carrying forward their responses for the initial interview to the subsequent five months in the survey 5 3 Sample Size The sample size of eligible persons in the LFS is determined so as to meet the statistical precision requirements for various labour force characteristics at the provincial and sub provincial level to meet the requirements of federal provincial and municipal governments as well as a host of other data users The monthly LFS sample consists of approximately 60 000 dwellings After excluding dwellings found to be vacant dwellings demolished or converted to non residential uses dwellings containing only ineligible persons dwellings under construction and seasonal dwellings about 54 000 dwellings remain which are occupied by one or more eligible persons From these dwellings LFS information is obtained for approximately 102 000 civilians aged 15 or over 5 4 Sample Rotation The LFS follows a rotating panel sample design in which households remain in the sample for six consecutive months The total sample consists of six representative sub samples or panels and each month a panel is replaced after completing its six month stay in the survey Outgoing households are replaced by households in the same or a similar area This results in a five sixths month to month sample overlap which makes the design efficient for estimating month to month ch
67. al person weight divided by the AVERAGE weight 4 perform the analysis for these respondents using the RESCALED weight However because the stratification and clustering of the sample s design are still not taken into account the variance estimates calculated in this way are likely to be under estimates The calculation of more precise variance estimates requires detailed knowledge of the design of the survey Such detail cannot be given in this microdata file because of confidentiality Variances that take the complete sample design into account can be calculated for many statistics by Statistics Canada on a cost recovery basis 9 5 Coefficient of Variation Release Guidelines Before releasing and or publishing any estimate from the Residential Telephone Service Survey users should first determine the quality level of the estimate The quality levels are acceptable marginal and unacceptable Data quality is affected by both sampling and non sampling errors as discussed in Chapter 8 However for this purpose the quality level of an estimate will be determined only on the basis of sampling error as reflected by the coefficient of variation as shown in the table below Nonetheless users should be sure to read Chapter 8 to be more fully aware of the quality characteristics of these data Special Surveys Division Residential Telephone Service Survey May 2003 User Guide First the number of respondents who contribute to the calculation
68. anges The rotation after six months prevents undue respondent burden for households that are selected for the survey Because of the rotation group feature it is possible to readily conduct supplementary surveys using the LFS design but employing less than the full size sample Special Surveys Division 15 Residential Telephone Service Survey May 2003 User Guide 5 5 Modifications to the Labour Force Survey Design for the Residential Telephone Service Survey The Residential Telephone Service Survey used five of the six rotation groups in the May 2003 LFS sample For the RTSS the coverage of the LFS was set at the household level However unlike the LFS where information is collected for all eligible household members the Residential Telephone Service Survey only collected information from one household member who reported about the household 5 6 Sample Size by Province for the Residential Telephone Service Survey The following table shows the number of household members in the LFS sampled rotations who were eligible for the Residential Telephone Service Survey supplement This table includes households which were non respondents to the LFS Province Sample Size Newfoundland and Labrador 1 638 Prince Edward Island 1 149 Nova Scotia 2 546 New Brunswick 2 364 Quebec 8 256 Ontario 12 866 Manitoba 3 189 Saskatchewan 3 265 Alberta 4 393 British Columbia 4 235 Canada 43 901 Special Surveys Division R
69. antic Provinces under 2 000 Prairie Provinces under 3 000 30 Special Surveys Division Residential Telephone Service Survey May 2003 User Guide 10 0 Approximate Sampling Variability Tables In order to supply coefficients of variation CV which would be applicable to a wide variety of categorical estimates produced from this microdata file and which could be readily accessed by the user a set of Approximate Sampling Variability Tables has been produced These CV tables allow the user to obtain an approximate coefficient of variation based on the size of the estimate calculated from the survey data The coefficients of variation are derived using the variance formula for simple random sampling and incorporating a factor which reflects the multi stage clustered nature of the sample design This factor known as the design effect was determined by first calculating design effects for a wide range of characteristics and then choosing from among these a conservative value usually the 75 percentile to be used in the CV tables which would then apply to the entire set of characteristics The table below shows the conservative value of the design effects as well as sample sizes and population counts by province which were used to produce the Approximate Sampling Variability Tables for the Residential Telephone Service Survey RTSS Province and Region Design Effect Sample Size Population Newfoundland and Labrador 1 512 197 514 Prince E
70. ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckok 1 7 0 350 Ok kk kk kk kk kk ok kk kk kk kk kk ck KK KA ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck k ck ckckck 0 9 NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION Special Surveys Division 47 Residential Telephone Service Survey May 2003 User Guide RESIDENTIAL TELEPHONE SERVICE SURVEY May 2003 Approximate Sampling Variability Tables Saskatchewan NUMERATOR OF 29 24 9 N N w gt BUA O N Ui io N J gt Q O to to N 0 O WM HM ooo oe a 10 0 NNN 4 00 O Q o 1 D Oi N 4S Oi XO No ANONA i04 O QQ O J G 01 2100010 O O 10000000000 oio O O O O O F F N Q Q dS Gn OY o CKCkckckckckckckckck ck kckck ck k ck k ck KA KA h k KA KA KA kckck ck KARA CKCkckckckck ck ck ck ck ckckckckckck ck kckckckckckckckck ck KA KA KA ck ck ck ck ck k ck CKCkckckckckckckckck ck k ck k ck k ck kok kckckckckckck ck KA KA ck ck ck ck ck ck ck ck ck CKCkckckckckckckckck ck k ck k ck kckck ck kckckckckckck ck KA KA KA KA ck ck ck ck ok ESTIMATED PERCENTAGE 15 0 39 28 29 Cn o Qn Q OY OY OO COo OO RO oio O O O O F PF N N 0 BRUON OY XO QQ 1 QQ O P Q Q OPERAN O 0 OA O UI O
71. ck ck ck ck ck ck ck ck ck ck ck ckckck 3 9 3 70 7 23 Ok kk kk kk kk ok kk kk kk kk kk kk ck KA KA KK KA ck ck ck ck RR 3 8 2 9 v 24 3 7 2 9 7 25 Ok kk kk kk kk kk kk kk kk kk kk kk ck ck KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck kckock 3 6 2 8 6 30 Ok kk kk kk kk kk ke kk kk kk kk kk ck kk KA KA ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck EEE BiG 5 35 Ok kk kk kk kk kk kk kk kk kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck Ok 2 4 40 Ok kk kk kk kk kk kk kk kk kk kk ck ck ck kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck c
72. ck ck kckok 1 0 10 0 9 Ond 0 4 5000 Ok kk kk kk kk Sk kk kk kk kk kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck kk 0 8 0 6 0 4 6000 Ok kk kk kk Sk kk kk kk kk kk kk kk ck KA ck ck KA ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckck 0 7 0 6 0 3 7000 Ok kk kk kk kk kk kk kk kk kk kk ck ck ck kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK SA 0 5 0 3 8000 Ok kk kk kk kk kk kok kk kk RR kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK k 0 5 0 3 9000 Ok Ck Ck kk kk kk kk kk kk kk kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck kckok 03 10000 Ok kk kk kk kk kk kk Sk kk kk kk kk ck ck kk ck KA KA ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck
73. ckckckckckckckckckck ck ck ROK KOK RT 30 0 36 1 255 20 9 8 1 6 2 4 7 Su 2 8 2 0 1 4 0 9 0 4 0 0 9 7 93 9 0 8 8 8 5 8 3 8 7 9 7 7 7 5 7 4 1 52 6 6 6 5 7 5 4 55 4 9 4 7 4 5 4 3 4 2 4 0 349 3 8 34 7 3 6 CKCkckckckck ck kckck ck ck ck k ck kckck ck kckck ck k ck k ck k ck k ck kckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckck ck ck ck ck ck ck ck ck 35 0 PRPRPPRPRENNW NWOT Oda RRR woo 3 Qn OY OO tio O I9 Q UI J to I Q XO 4S O P Q 4S OY O O IN AN OWN O Ui O OG Q N I9 Od DO C9 CO CO CO CJ ds ds ds uS uS dS UI UI Ui Oy J N N 1 OO OO OO OO to O 1 CKCkckckckckckck RARA RAR k ck k ck k ck k ck HH HH k ck kckckckck ck kckckckckckckckckckckckckckckckckckckckckckckckckckckckckck ck ckckckck ck HH RK RT CKCkckckckck ck ck ckck ck k ck kckckckck ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck kckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckck ck ck ck ckck ck ok CKCkckckckckckck ckck ck ck ckckckck ck ck ck k ck k ck k ck k ck kckck ck kckck ck k ck k ck kckckckckckckckckckck ck kckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckck ck ck ckck ck ok PERCENTAGE 1000 0 1 1 0 2 0 1 Kerken 43 0 42 7 2 30 4 30 2 3 24 8 24 7 4 21 4 5
74. da and other companies are from time to time negotiating local service pricing options for phone rates with the Canadian Radio Television and Telecommunication Commission Penetration rates are the most reliable indicator of affordability as there is no price range that can be identified as affordable or not affordable As a result the importance of monitoring any changes in phone penetration rates and analysing the reasons for non subscribers is necessary to properly guide regulators in decisions about rate increases decreases or subsidies Concern had been expressed in 1996 that the mechanism for monitoring penetration rates was not adequate in providing timely results to indicate whether Canadian penetration rates fall as a result of increases in local rates At that time data on penetration rates were available from the Household Facilities and Equipment Survey but only on an annual basis Given the changes that were and will be occurring in the basic residential telephone rates an annual survey was not adequate to accurately reflect the impact that these changes are having on Canadian telephone subscribership In 1996 Statistics Canada was approached by Stentor Resource Centre Inc to conduct a quarterly survey in order to monitor the phone residential penetration rates across Canada The management of the survey was transferred from Stentor to Bell Canada in the Fall of 1998 Since the year 2000 the survey has been conducted bi annually as a supp
75. dures that should be used In order for survey estimates and analyses to be free from bias the survey weights must be used While many analysis procedures found in statistical packages allow weights to be used the meaning or definition of the weight in these procedures differ from that which is appropriate in a sample survey framework with the result that while in many cases the estimates produced by the packages are correct the variances that are calculated are poor Approximate variances for simple estimates such as totals proportions and ratios for qualitative variables can be derived using the accompanying Approximate Sampling Variability Tables For other analysis techniques for example linear regression logistic regression and analysis of variance a method exists which can make the variances calculated by the standard packages more meaningful by incorporating the unequal probabilities of selection The method rescales the weights so that there is an average weight of 1 For example suppose that analysis of all male respondents is required The steps to rescale the weights are as follows 1 select all respondents from the file who reported SEX men 2 calculate the AVERAGE weight for these records by summing the original person weights from the microdata file for these records and then dividing by the number of respondents who reported SEX men 3 foreach of these respondents calculate a RESCALED weight equal to the origin
76. dward Island 1 071 53 866 Om aa 398H E All coefficients of variation in the Approximate Sampling Variability Tables are approximate and therefore unofficial Estimates of actual variance for specific variables may be obtained from Statistics Canada on a cost recovery basis Since the approximate CV is conservative the use of actual variance estimates may cause the estimate to be switched from one quality level to another For instance a marginal estimate could become acceptable based on the exact CV calculation Remember If the number of observations on which an estimate is based is less than 30 the weighted estimate is most likely unacceptable and Statistics Canada recommends not to release such an estimate regardless of the value of the coefficient of variation Special Surveys Division 31 32 Residential Telephone Service Survey May 2003 User Guide 10 1 How to Use the Coefficient of Variation Tables for Categorical Estimates The following rules should enable the user to determine the approximate coefficients of variation from the Approximate Sampling Variability Tables for estimates of the number proportion or percentage of the surveyed population possessing a certain characteristic and for ratios and differences between such estimates Rule 1 Estimates of Numbers of Households Possessing a Characteristic Aggregates The coefficient of variation depends only on the size of the estimate itself On the Ap
77. e column so it is necessary to use the figure closest to it namely 100 000 Similarly the percentage estimate does not appear as any of the column headings so it is necessary to use the figure closest to it 50 0 4 The figure at the intersection of the row and column used namely 5 6 is the coefficient of variation to be used 5 Sothe approximate coefficient of variation of the estimate is 5 696 The finding that 56 7 of households which did not have telephone service for their residence during the reference period could not afford telephone service can be published with no qualifications Example 3 Estimates of Differences Between Aggregates or Percentages Suppose that a user estimates that 796 352 3 103 651 25 7 of households in Quebec reported that their total annual income was less than the low income cut off LICO while 858 163 4 526 715 19 0 of households in Ontario reported that their total annual income was less than LICO How does the user determine the coefficient of variation of the difference between these two estimates 1 Using the QUEBEC and ONTARIO coefficient of variation tables in the same manner as described in Example 1 gives the CV of the estimate for households in Quebec as 2 895 and the CV of the estimate for households in Ontario as 3 5 Special Surveys Division 35 Residential Telephone Service Survey May 2003 User Guide NUMERATOR OF RESIDENTIAL TELEPHONE SERVICE SURVEY N
78. e Residential Telephone Service Survey Questionnaire The Residential Telephone Service Survey questionnaire was used in May 2003 to collect the information for the supplementary survey The file RTSS200305 QuestE pdf contains the English questionnaire This is a voluntary survey on telephone service How many different telephone numbers are there for your residence Include cellular phone numbers and phone numbers used for business INTERVIEWER Include phone numbers used for businesses even if the business is not within the residence or if the employer is paying for the person s phone service within that person s household This includes cell phones from work that are brought home Exclude pagers Di dein linet a aaah Go to RTS_Q02 1 2 3 or more R fUus8d tacite dit o eot qa Hye a dota av Edo Da qa Mya dada dei Go to RTS Q08 DON UKNOW inei rese fesevbia dial ada ode Go to RTS Q08 Go to RTS Q01C All respondents Is this number for a cellular phone or If RTS Q01B 2 or 3 then Are all of these numbers for cellular phones INTERVIEWER If the phone number is for both regular and cellular phone select No A regular phone can be with a cord or cordless Yes No Refused Don t know Go to RTS Q08 Respondents who have at least one phone number Special Surveys Division 59 RTS Q02 cO oo O S Note Coverage RTS_Q03 cO oo c gt N Note Coverage RTS_Q04 c
79. e of Human Resources Development Canada The intersections of the two types of regions form the first level of stratification for the LFS These ER EIER intersections are treated as primary strata and further stratification is carried out within them see Section 5 2 3 Note that a third set of regions census metropolitan areas CMA is also respected by stratification in the current LFS design since each CMA is also an EIER 5 2 2 Types of Areas The primary strata ER EIER intersections are further disaggregated into three types of areas rural urban and remote areas Urban and rural areas are loosely based on the Census definitions of urban and rural with some exceptions to allow for the formation of strata in some areas Urban areas include the largest CMAs down to the smallest villages categorized by the 1991 Census as urban 1 000 people or more while rural areas are made up of areas not designated as urban or remote A detailed description of the LFS design is available in the Statistics Canada publication entitled Methodology of the Canadian Labour Force Survey Catalogue no 71 526 XPB Special Surveys Division 13 Residential Telephone Service Survey May 2003 User Guide All urban areas are further subdivided into two types those using an apartment list frame and an area frame as well as those using only an area frame Approximately 1 of the LFS population is found in remote areas of provinces which are less acc
80. ecial Surveys Division Special Surveys Division Residential Telephone Service Survey May 2003 User Guide An example of a quantitative estimate is the average number of weeks for which employment insurance was collected for absences due to illness taken from an unemployment survey The numerator is an estimate of the total number of weeks for which employment insurance was collected for all persons experiencing an absence due to illness and its denominator is the number of persons reporting an absence due to illness Examples of Quantitative Questions Q How many consecutive weeks was this last absence _ _ Weeks work due to your own illness accident or pregnancy R Q How many separate periods of 2 or more weeks were you unable to R _ _ Periods 9 3 3 Tabulation of Categorical Estimates Estimates of the number of people with a certain characteristic can be obtained from the microdata file by summing the final weights of all records possessing the characteristic s of interest Proportions and ratios of the form X Y are obtained by a summing the final weights of records having the characteristic of interest for the numerator X 2 b summing the final weights of records having the characteristic of interest for the denominator 7 then c divide estimate a by estimate b x Y 9 3 4 Tabulation of Quantitative Estimates Estimates of quantities can be obtained from the microdata file by multiplying the
81. egies for rural areas were based not only on concentration of population but also on cost efficiency and interviewer constraints In each province remote settlements are sampled proportional to the number of dwellings in the settlement with no further stratification taking place Dwellings are selected using systematic sampling in each of the places sampled 5 2 4 Cluster Delineation and Selection Households in final strata are not selected directly Instead each stratum is divided into clusters and then a sample of clusters is selected within the stratum Dwellings are then sampled from selected clusters Different methods are used to define the clusters depending on the type of stratum Within each urban stratum in the urban area frame a number of geographically contiguous groups of dwellings or clusters are formed based upon 1991 Census counts These clusters are generally a set of one or more city blocks or block faces The selection of a sample of clusters always six or a multiple of six clusters from each of these secondary strata represents the first stage of sampling in most urban areas In some other urban areas census enumeration areas EA are used as clusters In the low density urban strata a three stage design is followed Under this design two towns within a stratum are sampled and then 6 or 24 clusters within each town are sampled For urban apartment strata instead of defining clusters the apartment building is
82. es held by Statistics Canada These differences are the result of actions taken to protect the anonymity of individual survey respondents Users requiring access to information excluded from the microdata files may purchase custom tabulations Estimates generated will be released to the user subject to meeting the guidelines for analysis and release outlined in Chapter 9 of this document Province Suppression of Geographic Identifiers The survey master data file includes explicit geographic identifiers for province and census metropolitan area It is also possible to obtain where sample sizes permit estimates by urban size class The survey public use microdata files usually do not contain any geographic identifiers below the provincial level However since the RTSS is a household based survey the variables CMA and urban size class are on the microdata file Special Surveys Division Residential Telephone Service Survey May 2003 User Guide 8 0 Data Quality 8 1 Response Rates The following table summarizes the response rates to the Labour Force Survey LFS and to the Residential Telephone Service Survey RTSS in May 2003 Household Household Household Number of response rate for response rate response respondents full LFS for LFS in RTSS rotations May 2003 1 2 3 4 and 6 Newfoundland and Labrador 94 3 Prince Edward Island Nova Scotia New Brunswick Qu bec Ontario Manitoba Saskatchewan Alberta Br
83. esidential Telephone Service Survey May 2003 User Guide 6 0 Data Collection Data collection for the Labour Force Survey LFS is carried out each month during the week following the LFS reference week The reference week is normally the week containing the 15 day of the month 6 1 Interviewing for the Labour Force Survey Statistics Canada interviewers are part time employees hired and trained to carry out the LFS and other household surveys Each month they contact the sampled dwellings to obtain the required labour force information Each interviewer contacts approximately 75 dwellings per month Dwellings new to the sample are usually contacted through a personal visit using the Computer assisted personal interview CAPI The interviewer first obtains socio demographic information for each household member and then obtains labour force information for all members aged 15 and over who are not members of the regular armed forces Provided there is a telephone in the dwelling and permission has been granted subsequent interviews are conducted by telephone This is done out of a centralized Computer assisted telephone interviewing CATI unit where cases are assigned randomly to interviewers As a result approximately 8596 of all households are interviewed by telephone In these subsequent monthly interviews the interviewer confirms the socio demographic information collected in the first month and collects the labour force information for
84. essible to LFS interviewers than other areas For administrative purposes this portion of the population is sampled separately through the remote area frame Some populations not congregated in places of 25 or more people are excluded from the sampling frame 5 2 3 Secondary Stratification In urban areas with sufficiently large numbers of apartment buildings the strata are subdivided into apartment frames and area frames The apartment list frame is a register maintained for the 18 largest cities across Canada The purpose of this is to ensure better representation of apartment dwellers in the sample as well as to minimize the effect of growth in clusters due to construction of new apartment buildings In the major cities the apartment strata are further stratified into low income strata and regular strata Where it is possible and or necessary the urban area frame is further stratified into regular strata high income strata and low population density strata Most urban areas fall into the regular urban strata which in fact cover the majority of Canada s population High income strata are found in major urban areas while low density urban strata consist of small towns that are geographically scattered In rural areas the population density can vary greatly from relatively high population density areas to low population density areas resulting in the formation of strata that reflect these variations The different stratification strat
85. estimate by the estimate itself and is expressed as a percentage of the estimate For example suppose that based upon the survey results one estimates that 1 596 of Canadian households did not have telephone service to their residence during the given month and this estimate is found to have a standard error of 0 00092 Then the coefficient of variation of the estimate is calculated as 0 00092 X 100 6 1 0 015 There is more information on the calculation of CV in Chapter 10 Special Surveys Division Residential Telephone Service Survey May 2003 User Guide 9 0 Guidelines for Tabulation Analysis and Release This Chapter of the documentation outlines the guidelines to be adhered to by users tabulating analysing publishing or otherwise releasing any data derived from the survey microdata files With the aid of these guidelines users of microdata should be able to produce the same figures as those produced by Statistics Canada and at the same time will be able to develop currently unpublished figures in a manner consistent with these established guidelines 9 1 Rounding Guidelines In order that estimates for publication or other release derived from these microdata files correspond to those produced by Statistics Canada users are urged to adhere to the following guidelines regarding the rounding of such estimates a Estimates in the main body of a statistical table are to be rounded to the nearest hundred units us
86. his adjustment factor is known as the stabilization weight The adjustment is done within stabilization areas defined as dwellings belonging to the same employment insurance economic region and the same rotation group Non response For certain types of non response i e household temporarily absent refusal data from a previous month s interview with the household if any is brought forward and used as the current month s data for the household Special Surveys Division 55 56 Residential Telephone Service Survey May 2003 User Guide In other cases non response is compensated for by proportionally increasing the weights of responding households The weight of each responding record is increased by the ratio of the number of households that should have been interviewed divided by the number that were actually interviewed This adjustment is done separately for non response areas which are defined by employment insurance economic region type of area and rotation group It is based on the assumption that the households that have been interviewed represent the characteristics of those that should have been interviewed within a non response area Labour Force Survey Sub weight The product of the previously described weighting factors is called the LFS sub weight All members of the same sampled dwelling have the same sub weight Sub provincial and Province Age Sex Adjustments The sub weight can be used to derive a valid estimate
87. hone Service Survey was programmed to appear on the list of surveys to be completed on the notebook computer after the demographic component for the LFS had been completed Any RTSS component not completed at the time the LFS was transmitted to one of the Statistics Canada regional offices was left incomplete and transmitted with the LFS 6 5 Non response to the Residential Telephone Service Survey For households responding to the LFS the next stage of data collection was to administer the Residential Telephone Service Survey In total 43 901 individuals were eligible for the supplementary survey the RTSS interview was completed for 39 924 of these individuals for a response rate of 90 9 More detailed information on response rates is presented in Chapter 8 Data Quality Special Surveys Division Residential Telephone Service Survey May 2003 User Guide 7 0 Data Processing The main output of the Residential Telephone Service Survey RTSS is a clean microdata file This Chapter presents a brief summary of the processing steps involved in producing this file 7 1 Data Capture Responses to survey questions are captured directly by the interviewer at the time of the interview using a computerized questionnaire The computerized questionnaire reduces processing time and costs associated with data entry transcription errors and data transmission The response data are encrypted to ensure confidentiality and sent via modem to the a
88. i to O1 Ov XO O lS Cn CKCkckckckckckck ck kckckckckckck ck k ck kckck ck KA KA KA KA KA KA KA KA ck ckck ck KARA CKOkckckckckckck ck k ck kckckck k ck k ck k ck KA KA KA KA KA KA KA KA KA ck ck ck ck ck ck ck ck ck 20 0 53 37 30 26 24 21 20 N Q C QQ 4S d U1 O1 t UI O OY OY ON ON d J O0 OO o to O O P P P N N N G Q Q dS S O1 O O N F2 S O0 4S O0 dS UI OY OO O S 4 OY XO o OY O G i O0 to I dS O OY O d OWON tO o O I 0 OD 0 10 0 o CKCkckckckck ck kckck ck kckck ck kckck ck kckckckckckckckck ck kckckckck ck KA KA KA KA KA KA KA ck ck ck ck ck ck ck CKCkckckckck ckck ck k ck k ck kckck ck k ck k ck k ck kok KA KA KA KA KA KA KA KA KA KA KA k ck kckck ck ck ck ok 25 0 51 36 29 254 ABs Ziy N o N N Q0 Q Q IS S t Q 1 O1 Q O OY OY Oy J J J O0 O0 tO O O O P p p pP N N WWW G G O OO OY O0 O I O N Q Q OY O0 O S AN O Q S 00 Ui d O OO Q O tO I O O gt X0 gt O O dS Q Q O S SG OONO CKCkckckckckckckckck RARA ck kckck ck k ck kckck ck kckckckckckckckckckckckckckckckckckckckckckckckckckckckck ck ck ckck ck ck ck ck kok 30 0 N NN N CO Cn DONUAUO a 4S Q O N O1 H O1 O Q i gt OY OO O MN Oi OO O1 tio Ui O N AN O N Ui O MN Oi to 4S O O1 a OO J O O1 4 HP QO BE N N NN Q Ys Ui Q 1 1 1 QI Or 000 2 1 J O0 iO O O O O F iz i N N IS UO Q BONOAN 2 35 0 NNN WwW Qo np BAN Bo 23
89. ible individuals in a dwelling are interviewed directly or by proxy this probability is essentially the same as the probability with which the dwelling is selected Cluster Sub weight The cluster delineation is such that the number of dwellings in the sample increases very slightly with moderate growth in the housing stock Substantial growth can be tolerated in an isolated cluster before the additional sample represents a field collection problem However if growth takes place in more than one cluster in an interviewer assignment the cumulative effect of all increases may create a workload problem In clusters where substantial growth has taken place sub sampling is used as a means of keeping interviewer assignments manageable The cluster sub weight represents the inverse of this sub sampling ratio in clusters where sub sampling has occurred Stabilization Weight Sample stabilization is also used to address problems with sample size growth Cluster sub sampling addressed isolated growth in relatively small areas whereas sample stabilization accommodates the slow sample growth over time that is the result of a fixed sampling rate along with a general increase in the size of the population Sample stabilization is the random dropping of dwellings from the sample in order to maintain the sample size at its desired level The basic weight is adjusted by the ratio of the sample size based on the fixed sampling rate to the desired sample size T
90. imits Although coefficients of variation are widely used a more intuitively meaningful measure of sampling error is the confidence interval of an estimate A confidence interval constitutes a statement on the level of confidence that the true value for the population lies within a specified range of values For example a 9596 confidence interval can be described as follows If sampling of the population is repeated indefinitely each sample leading to a new confidence interval for an estimate then in 95 of the samples the interval will cover the true population value Using the standard error of an estimate confidence intervals for estimates may be obtained under the assumption that under repeated sampling of the population the various estimates obtained for a population characteristic are normally distributed about the true population value Under this assumption the chances are about 68 out of 100 that the difference between a sample estimate and the true population value would be less than one standard error about 95 out of 100 that the difference would be less than two standard errors and about 99 out of 100 that the differences would be less than three standard errors These different degrees of confidence are referred to as the confidence levels Confidence intervals for an estimate X are generally expressed as two numbers one below the estimate and one above the estimate as x k X k where k is determined depending upon the
91. ing the normal rounding technique In normal rounding if the first or only digit to be dropped is 0 to 4 the last digit to be retained is not changed If the first or only digit to be dropped is 5 to 9 the last digit to be retained is raised by one For example in normal rounding to the nearest 100 if the last two digits are between 00 and 49 they are changed to 00 and the preceding digit the hundreds digit is left unchanged If the last two digits are between 50 and 99 they are changed to 00 and the preceding digit is incremented by 1 b Marginal sub totals and totals in statistical tables are to be derived from their corresponding unrounded components and then are to be rounded themselves to the nearest 100 units using normal rounding C Averages proportions rates and percentages are to be computed from unrounded components i e numerators and or denominators and then are to be rounded themselves to one decimal using normal rounding In normal rounding to a single digit if the final or only digit to be dropped is 0 to 4 the last digit to be retained is not changed If the first or only digit to be dropped is 5 to 9 the last digit to be retained is increased by 1 d Sums and differences of aggregates or ratios are to be derived from their corresponding unrounded components and then are to be rounded themselves to the nearest 100 units or the nearest one decimal using normal rounding e In instances where due to technical or
92. ion 43 Residential Telephone Service Survey May 2003 User Guide RESIDENTIAL TELEPHONE SERVICE SURVEY May 2003 Approximate Sampling Variability Tables New Brunswick NUMERATOR OF 10 0 45 6 32 3 26 4 22 8 20 4 8 6 1 23 6 1 542 4 4 3 8 3 2 2 7 2 2 1 28 1 4 lise 0 8 0 5 0 2 0 0 9 7 9 5 9 3 9d ESTIMATED PERCENTAGE 15 0 44 31 293 22 95 Te Ui F2 iO P2 N O1 XO N Oi OO O1 wo O 0 d1 0 0 I9 an OO co tO tO io io io O O O P P pP G gt 4 G O 0 0 20 0 43 0 30 4 24 8 21 5 9 2 7 6 6 3 932 4 3 3 6 3 0 2 4 1 9 1 5 T 0 8 0 4 0 9 9 9 6 9 4 9 2 9 0 8 8 8 6 Ted Tara 6 8 6 4 6 1 5 8 CKCkckckckckckck ck k ck k ck k ck k ck k ck k ck kckckckckckckckckckckckckckckckckckckckckckckckck ck KA KA KARA CKCkckckckckckck ck k k kekok ck k ck k ck kckck ck kok k k k ck KA KA KA KA KA KA k k KA KA KA ck ckck ck ck ck ok CKCkckckckckckck ck k ck kckckckck ck k ck k ck k ck KA KA KA KA KA KA KA KA 9 KA KA KA KA ck ck ck ckck ck ok 25 0 41 295 24 20 Cn MO S OY XO I OY O O Q O1 iO PB QQ OY O0 iS 00 IP O O O I ON 1 O O 0 P US O1 U1 OU Q OY O J J O0 OO OO CO Oo O tO tO O O O P F N N Q 0 BOUN o CKCkckckckckckck RARA ck k ck k ck k ck k ck k ck k ck k ck kckck ck kckckckckckckckck ck kckckckckckckckckck ck ck ck ck kckckckck ck ck ckok CKCkckckckckckckckck ck k ck k ck k ck k ck k ck k ck KA KA
93. ir total annual income was less than LICO The denominator of the estimate Xj is the number of households in Ontario which reported that their total annual income was less than LICO 2 Refer to the coefficient of variation tables for QUEBEC and ONTARIO see above 3 The numerator of this ratio estimate is 796 352 The figure closest to it is 750 000 The coefficient of variation for this estimate is found by referring to the first non asterisk entry on that row in the QUEBEC CV table namely 2 8 4 The denominator of this ratio estimate is 858 163 The figure closest to it is 750 000 The coefficient of variation for this estimate is found by referring to the first non asterisk entry on that row in the ONTARIO CV table namely 3 5 37 38 10 2 Residential Telephone Service Survey May 2003 User Guide 5 So the approximate coefficient of variation of the ratio estimate is given by Rule 4 which is BU 2 Qs 40 A where and G are the coefficients of variation of X and X respectively That is a 0 028 0 035 0 045 The obtained ratio of Quebec versus Ontario for households whose total annual income is less than the LICO is 796 352 858 163 which is 0 93 1 to be rounded according to the rounding guidelines in Section 9 1 The coefficient of variation of this estimate is 4 596 which is releasable with no qualifications How to Use the Coefficient of Variation Tables to Obtain Confidence L
94. itish Columbia Canada Response rate is the number of responding households as a percentage of the number of eligible households Response rate is the number of households responding to RTSS as a percentage of the number of households responding to or imputed by the LFS in the rotations sampled 8 2 Survey Errors The estimates derived from this survey are based on a sample of households Somewhat different estimates might have been obtained if a complete census had been taken using the same questionnaire interviewers supervisors processing methods etc as those actually used in the survey The difference between the estimates obtained from the sample and those resulting from a complete count taken under similar conditions is called the sampling error of the estimate Errors which are not related to sampling may occur at almost every phase of a survey operation Interviewers may misunderstand instructions respondents may make errors in answering questions the answers may be incorrectly entered on the questionnaire and errors may be introduced in the processing and tabulation of the data These are all examples of non sampling errors Over a large number of observations randomly occurring errors will have little effect on estimates derived from the survey However errors occurring systematically will contribute to biases in the survey estimates Considerable time and effort was made to reduce Special Surveys Division 21 2
95. k KK 3 5 3 4 uS 3 0 23 ph 350 Ok kk kk KA KA KA KK KA KK KK KK KK ck KK KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK k 353 3 2 3 0 2 8 2 1 1 2 400 Ok kk kk kk kk kk ke kk kk kk kk ck KK KK a a a ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK k 3 0 2 8 2 6 250 1 22 450 Ok kk kk kk kk KA KA KA KA KK kk ck ck ck ck KA ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckck 2 7 2 4 1 9 1 1 500 Ok kk kk kk kk kk kk kk kk ck ck ck kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck Ck ck ck ck Ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckck DUES 1 8 Ped 750 Ok kk kk kk kk KK KK KA KA KA KK KA KA KA KA KA ck ck ck ck KK KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckok 1 5 0 8 1000 Ok kk kk kk kk kk kk kk kk kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck SSS 0 7 NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION
96. k a KKK RK KKK KK RR KR RR RK 5 5 5 3 5 1 4 7 3 6 2l 6 Ok kk kk kk kk ok kk kk kk kk kk ck kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK en 5 4 5 2 5 0 4 5 3 25 20 7 Ok kk Ck kk kk kk kk kk kk kk kk ck KA KA KA KK ck ck ck ck ck KA ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckck 5 0 4 8 4 4 3 4 2 0 8 Ok kk kk kk kk kk kk kk kk ck kk kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckok 4 9 4 7 4 3 3 3 9 9 Ok kk kk kk Sk kk kk kk kk kk kk kk ck ck ck kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck OK OK 4 6 4 2 392 9 20 OK Ck kk kk kk kk kk kk kk kk kk kk ck ck kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckck 4 4 4 0 3 1 8 21 OK kk Ck kk kk kk kk kk kk kk kk kk ck KK ck kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KOR QS 4 3 4 0 3 1 8 22 Ok Ck Ck kk kk kk kk kk kk kk kk ck kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck
97. k ck ck ck ck ck ck ck ck ck ckckok 28 45 Ok kk kk kk kk kk kk kk kk kk kk ck ck ck kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck k ck ckckck 129 NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION 42 Special Surveys Division Residential Telephone Service Survey May 2003 User Guide RESIDENTIAL TELEPHONE SERVICE SURVEY May 2003 Approximate Sampling Variability Tables Nova Scotia NUMERATOR OF ESTIMATED PERCENTAGE PERCENTAGE 000 0 1 1 0 2 0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 70 0 90 0 T MAS OR EG 52 4 52 2 51 4 50 0 48 6 47 1 45 6 44 1 42 5 40 8 317 3 28 9 16 7 2 NONO AE uud 36 9 36 3 3523 34 4 33 3 32 3 31 2 30 0 28 9 26 3 20 4 11 8 3 VW REE 30 3 30 1 29 7 28 9 28 0 21 2 26 3 2545 24 5 23 6 21 5 16 7 9 6 4 SEN BALE LARS UE 26 1 25 7 25 0 24 3 23 6 22 8 22 0 21 2 20 4 8 6 14 4 8 3 5 RAS ee a RR 23 3 23 0 22 4 2147 21417 20 4 gt 9 0 Bs 6 7 12 9 dum 6 ERAN e 21 3 21 0 20 4 9 8 9 2 8 6 8 0 Tsa 6 7 542 11 8 6 8 7 SARA LS EARS EROR UE 1977 9 4 8 9 8 4 ESO 7 2 ez 6 1 5 4 4 1 10 9 6 53 8 ERAN KEE KLE RARE AAA RRE 852 7 1 7452 6 7 6 1 5 6 5 0 4 4 342 10 2 5 9 9 71 6 7 6 2 5 7 5
98. k kk Sk kk kk kk kk kk kk kk kk kk ck KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK SA 4 5 4 4 4 2 3 8 3 0 7 100 Ok kk kk kk kk KA KA a a a a KA KA KK KK RR KK KR RR k kk ik k kkk kkark k k kk ikik k 4 4 4 2 4 3 7 2 9 7 125 Ok kk kk kk Sk kk kk kk kk kk kk ck kk ck ck kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK k 3 8 37 Gu 2 6 35 150 Ok kk kk kk kk kk kk kk kk kk kk kk ck A KA KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck EAk 3 0 2 4 4 200 Ok Ck kk kk kk kk kk kk kk kk ck kk ck ck ck kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckck 2 2 250 Ck Ck kk kk k k kk KA KA KK KK KK KA KK KA KA KA KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck kok kok Ok 1 8 ad 300 Ok kk kk kk KA ok kk kk kk kk kk kk kk a ck ck ck ck KA KA KA KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ne en 0 NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION Special Surveys Divis
99. kck ck ck ck ck ck AAA PERCENTAGE 000 0 1 1 0 2 0 5 0 1 FOO 47 9 47 6 46 9 2 FOO 33 8 39 57 33 2 3 27 5 27 1 4 23 8 23 4 5 2153 21 0 6 ck ck k k ck k k k k k k k k k k k k k K A A A 19 1 7 ck ck k k ck k k k k k k k k k k k k k k k k KKK 17 7 8 ck ck k ck k k k k k k k k k k k k k k k k k k k k 16 6 9 ck ck k k k k k k k k k k k k k k k k k k k KKK 15 6 0 ck ck ck k ck k k k k k k k k k k k k k k k k AA 14 8 1 ck ck k k ck k k k k k k k k k k k k k k k k KKK 14 1 2 1535 5 3 ck ck k k k k k k k k k k k k k k k SG KKK 13 0 4 ck ck k ck k k k k k k k k k k k k k k k k k k KK 12 45 5 ck ck k k ck k k k k k k k k k k k k k k k k k k k k k AA 6 ck ck k k ck k k k k k K k k k k K k k k k k k k k k k k k k k k K 7 ck ck k k k k k k k k k k k k k k k k k k k k k k k k k k k k k K 8 ck k ck k K k k k k k k k k k k k k k k k k k k k k k k k k k k K 9 ck ck k k K k k k k k k k k k k k k k k k k k k k k k k k k k k K 20 ck ck k k k k k k k k K k k k k k k k k k k k k k k k k k k k k K ale ck ck ck k k k k k k KKK k k k k k k k k k k k k k k k AA 22 ck ck k k k k k K k k K k k k k k k k k k k k k k k k k k k k k K 23 ck ck k k k k k k k k k k k k k k k k k k k k k k k k k k
100. kk kk kk ck ck ck ck kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckck 2 0 zu 150 Ok kk kk kk kk kk kk Sk kk kk kk kk ck ck ck ck ck ck ck KA ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck k ck ck ckok 0 NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION Special Surveys Division 41 Residential Telephone Service Survey May 2003 User Guide RESIDENTIAL TELEPHONE SERVICE SURVEY May 2003 Approximate Sampling Variability Tables Prince Edward Island NUMERATOR OF ESTIMATED PERCENTAGE PERCENTAGE 000 0 1 1 0 2 0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 70 0 90 0 1 RARE OR OR OE KBAR ARE 254 3 25 0 24 3 23 6 22 9 22 2 21 4 20 6 19 8 18 1 14 0 854 2 WO qM a 17 6 TT 2 16 7 16 2 15 7 15 1 14 6 14 0 12 8 9 9 5 7 3 14 0 13 6 4 3 2 12 8 TALA 11 9 11 5 10 5 8 1 4 7 4 1241 11 8 1155 TT TY 10 7 10 3 9 9 9 1 XE 4 0 5
101. kkkkkkkk kkkkkkkxk kkkkkkkk 0 3 NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION 4 So the approximate coefficient of variation of the estimate is 5 6 The 34 finding that 177 859 to be rounded according to the rounding guidelines in Section 9 1 households did not have telephone service for their residence during the reference period is publishable with no qualifications Special Surveys Division Residential Telephone Service Survey May 2003 User Guide Example 2 Estimates of Proportions or Percentages of Households Possessing a Characteristic Suppose that the user estimates that 100 791 177 859 56 7 of households which did not have telephone service for their residence during the reference period reported that they could not afford telephone service How does the user determine the coefficient of variation of this estimate 1 Refer to the coefficient of variation table for CANADA see above 2 Because the estimate is a percentage which is based on a subset of the total population i e households which did not have telephone service for their residence during the reference period it is necessary to use both the percentage 56 7 and the numerator portion of the percentage 100 791 in determining the coefficient of variation 3 The numerator 100 791 does not appear in the left hand column the Numerator of Percentag
102. l 3 9 2 3 150 RECA RARE REPASA 6 5 6 4 6 2 6 1 5 9 55 5 5 5 3 51T 4 6 3 6 2v 200 ee EE OK o stole 5 6 555 5 4 5272 pul 4 9 4 8 4 6 4 4 4 0 Ju 1 8 250 ECKE KK GE X ok sek RIES ales e 5 0 4 8 4 7 4 6 4 4 4 3 4 1 3 9 3 6 2748 1 6 300 i NIT SK TPE RAS ER A 4 5 4 4 4 3 4 2 4 0 3 9 did 3 6 3 3 2 5 1 5 350 4 2 dT 4 0 3 8 3 3 6 3 5 3 3 3 0 2 4 1 4 400 DENSI GA Sf SE En En ORA UK 29 3 8 3 7 3 6 34 5 3 4 Jue Jud 2 8 252 13 450 Ok Ck Ck kk kk kk KKK KKK KK ck ck kk KKK 3 7 3 6 3 5 3 4 3 3 3 2 3 1 2 9 EN Dir 14 2 500 e GENE REA eO RUE 33 5 3 4 3 3 32 Sek 3 0 2 9 2 8 2 5 2 0 1 1 750 Ok Ck Ck KKK KKK KK KK KKK KKK KKK ckck ck ck KKK 2 8 2 2 6 2 5 2 5 2 4 2 3 DEN 1 6 0 9 1000 2 4 2 3 243 22 Der 21 2 0 1 8 1 4 0 8 1500 Ok Ck kk kk kk kk A KK KA KK KK KK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK 1 9 1 9 1 8 17 1 7 1 6 1 5 1 0 7 2000 Ok kk KKK KKK KK KK KK KK KK KK RK KK KK KK zn 1 6 1 6 1 5 1 5 1 4 1 73 1 0 0 6 3000 Ok kk kk kk kk kk kk kk kk ck kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KK en 1 43 1 2 1 2 1 1 1 0 0 8 0 5 4000 Ok kk kk kk kk kk Sk kk kk kk kk kk kk ck a a KA ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck
103. led by the phone company Moved and can t afford the installation price Lost job Unemployed I m on any form of social assistance etc The following answers should be coded to Moved Respondent moved on vacation going south for the winter moved and don t want need the phone anymore etc The following answers should be coded to Any other response Sharing a phone receiving harassing calls getting a private number hard of hearing dissatisfied with the phone company don t want other household members to receive calls etc Respondents whose reason for not having a phone is because they cancelled it RTS_Q02 1 l am going to read a list of most common charges which could be on a telephone bill Please tell me which of these charges you find difficult to afford INTERVIEWER Read categories to respondent Mark all that apply The installation charge The security deposit Monthly charge for your basic phone line which includes local calls Optional features and or set charges Long distance charges Other usage charges i e 900 service features directory assistance etc Refused Don t know Respondents who cannot afford a phone RTS Q02 2 or RTS_Q03 2 Special Surveys Division RTS Q05 cO OO N Coverage RTS_Q06 oon Coverage RTS Q07 Residential Telephone Service Survey May 2003 User Guide If there were an emergency at home would members of your household have easy access to a neighbour s
104. lement to the Labour Force Survey Special Surveys Division 7 Residential Telephone Service Survey May 2003 User Guide 3 0 Objectives There are two main objectives which Bell Canada has outlined They are 1 to collect information on penetration rates across Canada and make them available by province and 2 to collect information on non subscriber characteristics To accommodate these goals and to ensure that the survey is focused on fulfilling these objectives Bell Canada submitted an analysis plan which outlined their data needs This plan was used to design the questionnaire and to justify the variables requested Special Surveys Division 9 Residential Telephone Service Survey May 2003 User Guide 4 0 Concepts and Definitions This Chapter outlines concepts and definitions of interest to the users Users are referred to Chapter 12 of this document for a copy of the actual survey forms used Number of telephone numbers for the residence Includes cellular telephone numbers and telephone numbers used for business even if the business is not within the residence or if the employer is paying for the person s telephone service It includes cellular telephones from work that are brought home Pagers are excluded Income Household income has been measured against the 1992 base Statistics Canada Low Income Cut Offs LICO see Income Statistics Division publication Low Income Cutoffs from 1992 to 2001 and Low Income
105. level of confidence desired and the sampling error of the estimate Confidence intervals for an estimate can be calculated directly from the Approximate Sampling Variability Tables by first determining from the Special Surveys Division Residential Telephone Service Survey May 2003 User Guide appropriate table the coefficient of variation of the estimate X and then using the following formula to convert to a confidence interval CI CI x 1Xa 1Xa where Os is the determined coefficient of variation of X and t 1 if a 6896 confidence interval is desired t 1 6 if a 9096 confidence interval is desired t 2 if a 95 confidence interval is desired t 2 6 if a 99 confidence interval is desired Note Release guidelines which apply to the estimate also apply to the confidence interval For example if the estimate is not releasable then the confidence interval is not releasable either 10 2 1 Example of Using the Coefficient of Variation Tables to Obtain Confidence Limits A 95 confidence interval for the estimated proportion of households which did not have telephone service for their residence during the reference period because they could not afford telephone service from Example 2 Section 10 1 1 would be calculated as follows X 56 7 or expressed as a proportion 0 567 t 2 Qi 5 6 0 056 expressed as a proportion is the coefficient of variation of this estimate as determined from the tables
106. mates Please be warned that these estimates flagged with the letter U do not meet Statistics Canada s quality standards Conclusions based on these data will be unreliable and most likely invalid Special Surveys Division 29 Residential Telephone Service Survey May 2003 User Guide 9 6 Release Cut off s for the Residential Telephone Service Survey The following table provides an indication of the precision of population estimates as it shows the release cut offs associated with each of the three quality levels presented in the previous section These cut offs are derived from the coefficient of variation CV tables discussed in Chapter 10 For example the table shows that the quality of a weighted estimate of 5 000 people possessing a given characteristic in Newfoundland and Labrador is marginal Note that these cut offs apply to estimates of population totals only To estimate ratios users should not use the numerator value nor the denominator in order to find the corresponding quality level Rule 4 in Section 10 1 and Example 4 in Section 10 1 1 explains the correct procedure to be used for ratios Province and Region Acceptable Marginal Unacceptable CV 0 0 16 5 CV 16 6 33 3 CV gt 33 3 Prince Edward Island 500 to lt 2 500 under 500 New Brunswick 8 500 over to lt under 2 000 Manitoba under 2 500 Saskatchewan under 1 500 Alberta 19 500 amp over to lt under 5 000 British Columbia under 5 600 Atl
107. n 3 7 3 4 2 6 5 75 OK Ck Ck kk kk kk kk kk Sk kk kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckck 32 6 aug 2 5 5 80 Ok kk kk kk kk kk kk kk kk kk kk kk kk kk KK KA KK KA ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck AKO QK 3 2 2 5 4 85 Ok kk kk kk kk kk kk kk kk kk kk ck kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck kckck 3 1 2 4 4 90 Ok kk kk kk kk Sk kk kk kk kk ck ck kk ck ck A KA KA KA ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck k ck ckckock 3 0 2 3 3 95 Ok kk kk kk kk kk kk kk kk kk kk ck kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck kckok 2 9 ECT 3 100 Ok kk kk kk kk kk kk kk kk ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck k ck ckckck 2 2 3 125 Ok Sk kk kk kk kk kk kk
108. n or percentage is based upon a subset of the total population e g those in a particular province or census metropolitan area reference should be made to the proportion or percentage across the top of the table and to the numerator of the proportion or percentage down the left side of the table The intersection of the appropriate row and column gives the coefficient of variation Rule 3 Estimates of Differences Between Aggregates or Percentages The standard error of a difference between two estimates is approximately equal to the square root of the sum of squares of each standard error considered separately That is the standard error of a difference X X is ge Jo a y where X is estimate 1 X is estimate 2 and and G are the coefficients of variation of X and X respectively The coefficient of variation of d is given by O 1d This formula is accurate for the difference between separate and uncorrelated characteristics but is only approximate otherwise Special Surveys Division Residential Telephone Service Survey May 2003 User Guide Rule 4 Estimates of Ratios In the case where the numerator is a subset of the denominator the ratio should be converted to a percentage and Rule 2 applied This would apply for example to the case where the denominator is the number of households which did not have telephone service for their residence during the reference period and the numerator i
109. not understand or misinterpreted a question refused to answer a question or could not recall the requested information Item non response is usually very low for the RTSS Questions Q01C Q02 Q03 Q041 Q042 Q043 Q044 Q045 and Q046 all had non response rates which were less than 1 496 Question Q08 which was the income class question had a non response rate of 3 996 which is considered to be quite low especially for an income related question 8 2 5 Measurement of Sampling Error Since it is an unavoidable fact that estimates from a sample survey are subject to sampling error sound statistical practice calls for researchers to provide users with some indication of the magnitude of this sampling error This section of the documentation outlines the measures of sampling error which Statistics Canada commonly uses and which it urges users producing estimates from this microdata file to use also The basis for measuring the potential size of sampling errors is the standard error of the estimates derived from survey results Special Surveys Division 23 24 Residential Telephone Service Survey May 2003 User Guide However because of the large variety of estimates that can be produced from a survey the standard error of an estimate is usually expressed relative to the estimate to which it pertains This resulting measure known as the coefficient of variation CV of an estimate is obtained by dividing the standard error of the
110. o 0 while the CMAs remain the same A size of area of residence variable was also created This variable provides a population size code based on 1991 Census definitions for every urban non urban area in the Labour Force Survey LFS sample frame 7 5 Weighting The principle behind estimation in a probability sample such as the LFS is that each person in the sample represents besides himself or herself several other persons not in the sample For example in a simple random 296 sample of the population each person in the sample represents 50 persons in the population The same principle also applies to households The weighting phase is a step which calculates for each record what this number is This weight appears on the microdata file and must be used to derive meaningful estimates from the survey For example if the number of households with one or more telephone numbers Special Surveys Division 19 20 Residential Telephone Service Survey May 2003 User Guide for their residence is to be estimated it is done by selecting the records referring to those households in the sample with that characteristic and summing the weights entered on those records Details of the method used to calculate these weights are presented in Chapter 11 7 6 Suppression of Confidential Information It should be noted that the Public Use microdata files described above differ in a number of important respects from the survey master fil
111. one Service Survey 18 6 5 Non response to the Residential Telephone Service Survey 18 DrcWuee rrtig ne 19 7 1 Data Capture xL 19 7 2 EQUINOS nis cc 19 7 3 Coding of Open ended Questions pp 19 7 4 Creation of Derived Variables sse entere nnne nns 19 7 5 tures d 19 7 6 Suppression of Confidential Information sess 20 DataGuality coma E T E E 21 8 1 Response RIES we 21 8 2 SUrVvey EIrorS u oni eae 21 8 2 1 The Fraime ee ii 22 8 2 2 Data Collection 2 tice i alertaba 22 8 2 3 Data rete mai i TEESE AAE EE RRENA EEATT EIERNE EPERERA 22 8 2 4 NornsrespOrtlse teretes tace ences d eto i tea ad 23 8 2 5 Measurement of Sampling Error essen 23 Special Surveys Division 3 9 0 10 0 12 0 13 0 Residential Telephone Service Survey May 2003 User Guide Guidelines for Tabulation Analysis and Release eese 25 9 1 Rounding Guidelines De NEE 25 9 2 Sample Weighting Guidelines for Tabulation pp 26 9 3 Definitions of Types of Estimates Categorical and Quantitative 26 9 3 1 Gategorical Estimates n ere dai 26 9 3 2 Quantitative Estimates aeree dd dd nr 26 9 3 3 Tabulation of Categorical Estimates essen 27 9 3 4
112. other limitations a rounding technique other than normal rounding is used resulting in estimates to be published or otherwise released which differ from corresponding estimates published by Statistics Canada users are urged to note the reason for such differences in the publication or release document s f Under no circumstances are unrounded estimates to be published or otherwise released by users Unrounded estimates imply greater precision than actually exists Special Surveys Division 25 26 Residential Telephone Service Survey May 2003 User Guide 9 2 Sample Weighting Guidelines for Tabulation The sample design used for the Residential Telephone Service Survey RTSS was not self weighting When producing simple estimates including the production of ordinary statistical tables users must apply the proper sampling weight If proper weights are not used the estimates derived from the microdata files cannot be considered to be representative of the survey population and will not correspond to those produced by Statistics Canada Users should also note that some software packages may not allow the generation of estimates that exactly match those available from Statistics Canada because of their treatment of the weight field 9 3 Definitions of Types of Estimates Categorical and Quantitative Before discussing how the Residential Telephone Service Survey data can be tabulated and analysed it is useful to describe the two
113. ow 17 4 813 8 Refused 10 1 194 9 Not stated 8 2 747 39 924 12 191 305 Coverage Respondents who have at least one phone number Note If the phone number is for both regular and cellular phone select No A regular phone can be with a cord or cordless Variable Name Q02 Position 7 Length 1 Why don t you have a phone FREQ WTD 1 I cancelled it 57 13 539 2 Can t afford it 354 93 279 3 Moved 28 7 801 4 All other responses 130 36 954 6 Valid skip 39 337 12 035 196 7 Don t know 12 3 719 8 Refused 6 817 39 924 12 191 305 Coverage Respondents who do not have phones RTS Q01B 0 Special Surveys Division 65 Residential Telephone Service Survey May 2003 User Guide Residential Telephone Service Survey May 2003 Public Use Microdata File Variable Name Q03 Position 8 Length Why did you cancel it FREQ WTD 1 Can t afford it 21 4 414 2 Moved 6 1 586 3 All other responses 24 6 240 6 Valid skip 39 849 12 173 230 7 Don t know 2 411 8 Refused 3 473 9 Not stated 19 4 951 39 924 12 191 305 Coverage Respondents whose reason for not having a phone is because they cancelled it RTS Q02 1 Variable Name Q041 Position 9 Length 1 am going to read a list of most common charges which could be on a telephone bill Please tell me which of these charges you find difficult to afford The installation charge FREQ WTD 1 Yes 274 71 919 6 Valid skip 39 615 12 110 482 7 Don t know 8 2 597 8 Refused 3 473 9
114. people Adjustments 1 and 2 are taken into account by multiplying the LFS sub weight for each responding Residential Telephone Service Survey record by sum of LFS sub weights from each household responding to LFS sum of LFS sub weights from each household responding to the RTSS to obtain a non response adjusted Residential Telephone Service Survey sub weight WEIGHT1 This adjustment is performed at the province stratum level Adjustment 3 is calculated by multiplying WEIGHT1 for each Residential Telephone Service Survey respondent by known population total for province household size sum of weight WEIGHT 1 for responding household in province household size The resulting weight FINWT is the final weight which appears on the Residential Telephone Service Survey microdata file Special Surveys Division 57 12 0 RTS_101 RTS_Q01B cO oo Q E O Default Coverage RTS_Q01C oon Default Coverage Residential Telephone Service Survey May 2003 User Guide Questionnaires 12 1 The Labour Force Survey Questionnaire The Labour Force Survey Questionnaire LFS_QuestE pdf is used to collect information on the current and most recent labour market activity of all household members 15 years of age or older It includes questions on hours of work job tenure type of work reason for hours lost or absent job search undertaken availability for work and school attendance 12 2 Th
115. ppropriate Statistics Canada Regional Office From there they are transmitted over a secure line to Ottawa for further processing In total 40 985 documents were captured and transmitted for the survey 7 2 Editing The first type of error treated was errors in questionnaire flow where questions which did not apply to the respondent and should therefore not have been answered were found to contain answers In this case a computer edit automatically eliminated superfluous data by following the flow of the questionnaire implied by answers to previous and in some cases subsequent questions The second type of error treated involved a lack of information in questions which should have been answered For this type of error a non response or not stated code was assigned to the item 7 3 Coding of Open ended Questions No data items on the questionnaire were recorded by interviewers in an open ended format A total of two partially open ended questions were included in the survey These were items relating to reasons households do not have telephone service for their residence and why they cancelled their telephone service 7 4 Creation of Derived Variables A number of data items on the microdata file have been derived by combining items on the questionnaire in order to facilitate data analysis The variable CMA for example is actually a combination of census metropolitan area CMA and census agglomeration CA The CAs have been recoded t
116. proximate Sampling Variability Table for the appropriate geographic area locate the estimated number in the left most column of the table headed Numerator of Percentage and follow the asterisks if any across to the first figure encountered This figure is the approximate coefficient of variation Rule 2 Estimates of Proportions or Percentages of Households Possessing a Characteristic The coefficient of variation of an estimated proportion or percentage depends on both the size of the proportion or percentage and the size of the total upon which the proportion or percentage is based Estimated proportions or percentages are relatively more reliable than the corresponding estimates of the numerator of the proportion or percentage when the proportion or percentage is based upon a sub group of the population For example the proportion of households which did not have telephone service for their residence during the reference period is more reliable than the estimated number of households which did not have telephone service for their residence during the reference period Note that in the tables the coefficients of variation decline in value reading from left to right When the proportion or percentage is based upon the total population of the geographic area covered by the table the CV of the proportion or percentage is the same as the CV of the numerator of the proportion or percentage In this case Rule 1 can be used When the proportio
117. rges which could be on a telephone bill Please tell me which of these charges you find difficult to afford Optional features and or set charges FREQ WTD 4 Yes 142 37 074 6 Valid skip 39 747 12 145 327 7 Don t know 8 2 597 8 Refused 3 473 9 Not stated 24 5 835 39 924 12 191 305 Coverage Respondents who cannot afford a phone RTS_Q02 2 or RTS Q03 2 Variable Name Q045 Position 13 Length 1 am going to read a list of most common charges which could be on a telephone bill Please tell me which of these charges you find difficult to afford Long distance charges FREQ WTD 5 Yes 148 33 095 6 Valid skip 39 741 12 149 306 7 Don t know 8 2 597 8 Refused 3 473 9 Not stated 24 5 835 39 924 12 191 305 Coverage Respondents who cannot afford a phone RTS_Q02 2 or RTS Q03 2 68 Special Surveys Division Residential Telephone Service Survey May 2003 User Guide Residential Telephone Service Survey May 2003 Public Use Microdata File Q046 Position 14 Variable Name Length 2 am going to read a list of most common charges which could be on a telephone bill Please tell me which of these charges you find difficult to afford Other usage charges i e 900 service features directory assistance etc FREQ WTD 06 Yes 86 19 157 96 Valid skip 39 803 12 163 244 97 Don t know 8 2 597 98 Refused 3 473 99 Not stated 24 5 835 39 924 12 191 305 Coverage Respondents who cannot afford a phone RTS_Q
118. rom work would be greater than the coefficient of variation of the corresponding proportion of paid workers with an absence Hence if the coefficient of variation of the proportion is not releasable then the coefficient of variation of the corresponding quantitative estimate will also not be releasable Coefficients of variation of such estimates can be derived as required for a specific estimate using a technique known as pseudo replication This involves dividing the records on the microdata files into subgroups or replicates and determining the variation in the estimate from replicate to replicate Users wishing to derive coefficients of variation for quantitative estimates may contact Statistics Canada for advice on the allocation of records to appropriate replicates and the formulae to be used in these calculations Special Surveys Division Residential Telephone Service Survey May 2003 User Guide 10 5 Coefficient of Variation Tables RESIDENTIAL TELEPHONE SERVICE SURVEY May 2003 Approximate Sampling Variability Tables Newfoundland and Labrador NUMERATOR OF ESTIMATED PERCENTAGE PERCENTAGE 000 0 1 1 0 2 0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 70 0 90 0 1 i AN 3959 39 7 39 T 38 0 37 0 35 9 34 7 33 5 32 3 3d d 28 3 22 0 12 7 2 WORSE GORGE bio Sas sa 28 1 27 6 26 9 26 25 4 24 6 234 22 9 22 0 20 0 1545 950 3 AREA RAS ER RANA 22 9 22 6 22 0 21 3 20 7 20 0 19 4 LS 14 9 16 4 12 77 Le 3 4 EON
119. rs of eligible households For individuals who at first refuse to participate in the LFS a letter is sent from the Regional Office to the dwelling address stressing the importance of the survey and the household s cooperation This is followed by a second call or visit from the interviewer For cases in which the timing of the interviewer s call or visit is inconvenient an appointment is arranged to call back at a more convenient time For cases Special Surveys Division 17 Residential Telephone Service Survey May 2003 User Guide in which there is no one home numerous call backs are made Under no circumstances are sampled dwellings replaced by other dwellings for reasons of non response Each month after all attempts to obtain interviews have been made a small number of non responding households remain For households non responding to the LFS and for which LFS information was obtained in the previous month this information is brought forward and used as the current month s LFS information No supplementary survey information is collected for these households 6 4 Data Collection Modifications for the Residential Telephone Service Survey Information for the Residential Telephone Service Survey RTSS was obtained from a knowledgeable household member Upon completion of the Labour Force Survey interview the interviewer introduced the RTSS and proceeded with the interview with the respondent s permission The Residential Telep
120. s are different than the results obtained from the current survey and are only to be used as a guide Example 1 Estimates of Numbers of Households Possessing a Characteristic Aggregates Suppose that a user estimates that 177 859 households did not have telephone service for their residence during the reference period How does the user determine the coefficient of variation of this estimate 1 Refer to the coefficient of variation table for CANADA 2 The estimated aggregate 177 859 does not appear in the left hand column the Numerator of Percentage column so it is necessary to use the figure closest to it namely 200 000 Special Surveys Division 33 Residential Telephone Service Survey May 2003 User Guide 3 The coefficient of variation for an estimated aggregate is found by referring to the first non asterisk entry on that row namely 5 6 NUMERATOR OF RESIDENTIAL TELEPHONE SERVICE SURVEY NOVEMBER 2002 Approximate Sampling Variability Tables Canada ESTIMATED PERCENTAGE PERCENTAGE 000 0 1 1 0 2 0 5 0 10 0 15 0 20 096 35 0 40 0 50 096 70 0 90 0 1 79 3 79 0 78 6 77 4 75 3 73 2 71 0 64 0 61 5 56 1 43 5 25 1 2 56 1 55 8 55 6 54 7 53 2 51 7 50 2 45 3 43 5 39 7 30 7 17 7 3 45 8 45 6 45 4 44 7 43 5 42 3 41 0 36 9 35 5 32 4 25 1 145 4 39 7 39 5 39 3 38 7 37 7 36 6 35 5 32 0 30 7 28 1 21 7 12 6 5 35 5 35 3 35 1 34 6 33 7 32 7 31 8 28 6 27 5 25 1 19 4 11 2 50 HE 11 2 11 1 10 9 10 6 10 3
121. s from the frame which for one reason or another did not Special Surveys Division Residential Telephone Service Survey May 2003 User Guide have corresponding RTSS records These records were considered to be non responding records and were used in the weighting process to adjust for non response Data processing of the RTSS was straightforward since there were only nine questions on the CAI application Any record that contained a refusal or don t know in the first question Q01B was coded as a non response Note that 1 036 records were treated this way Since the data was collected using a CAI instrument data quality before processing was very high Very few changes were made to the data during editing No imputation was done for this survey 8 2 4 Non response A major source of non sampling errors in surveys is the effect of non response on the survey results The extent of non response varies from partial non response failure to answer just one or some questions to total non response Total non response occurred because the interviewer was either unable to contact the respondent no member of the household was able to provide the information or the respondent refused to participate in the survey Total non response was handled by adjusting the weight of households who responded to the survey to compensate for those who did not respond In most cases partial non response to the survey occurred when the respondent did
122. s the number of households which did not have telephone service to their residence during the reference period because they could not afford it In the case where the numerator is not a subset of the denominator as for example the ratio of the number of households in Quebec whose total annual income for 2002 was below the low income cut off as compared to the number of households in Ontario whose total annual income for 2002 was below the low income cut off the standard deviation of the ratio of the estimates is approximately equal to the square root of the sum of squares of each coefficient of variation considered separately multiplied by R That is the standard error of a ratio R 2 12 is D 2 2 o RG 0 where and G are the coefficients of variation of X and X respectively The coefficient of variation of R is given by OA IR The formula will tend to overstate the error if x and x are positively correlated and understate the error if X and a are negatively correlated Rule 5 Estimates of Differences of Ratios In this case Rules 3 and 4 are combined The CVs for the two ratios are first determined using Rule 4 and then the CV of their difference is found using Rule 3 10 1 1 Examples of Using the Coefficient of Variation Tables for Categorical Estimates The following examples based on the November 2002 survey are included to assist users in applying the foregoing rules Please note that the data for these example
123. s to Do a T test Let us suppose that the user wishes to test at 596 level of significance the hypothesis that there is no difference between the proportion of households in Quebec which reported that their total annual income was less than the low income cut off LICO and the proportion of households in Ontario which reported that their total annual income was less than LICO From Example 3 Section 10 1 1 the standard error of the difference between these two estimates was found to be 0 0098 Hence X X 0 257 0 190 _ 0 067 0 0 0098 0 0098 d t 6 84 Since t 6 84 is greater than 2 it must be concluded that there is a significant difference between the two estimates at the 0 05 level of significance 10 4 Coefficients of Variation for Quantitative Estimates For quantitative estimates special tables would have to be produced to determine their sampling error Since all of the variables for the Residential Telephone Service Survey are primarily categorical in nature this has not been done As a general rule however the coefficient of variation of a quantitative total will be larger than the coefficient of variation of the corresponding category estimate i e the estimate of the number of persons contributing to the quantitative estimate If the corresponding category estimate is not releasable the quantitative estimate will not be either For example the coefficient of variation of the total number of weeks absent f
124. un st Zei a tue EA CN OR SIUS QA 9 8 9 6 953 9 0 8 7 8 4 8 0 Tea 557 Jia 2 BE RR Apa uso CORO SK ES 9 9 9 6 9 3 9 1 8 8 8 5 8 2 7 8 Fiz 5 5 3 2 23 9 7 9 4 9 1 8 9 8 6 8 3 8 0 TET 7 0 5 4 3 1 24 AEN RACE IEA KE OK Roe AE 955 952 8 9 8 7 8 4 8 1 7 8 T5 6 9 2543 3l 25 Ba ne Koo NUR pk oh Dee 933 9 0 8 8 8 5 8 2 8 0 List 7 4 6 7 5 2 3 0 30 AS qo oS 8 5 8 2 8 0 7 8 T5 Teg 7 0 6 7 6 1 4 8 2 1 35 7 8 7 6 7 4 TED 7 0 6 7 6 5 6 2 5 7 4 4 2 5 40 7 3 T 3 6 9 6 7 6 5 6 3 6 1 5 8 53 4 2 4 45 AR eoe s vele oe 6 9 647 6 5 6 3 el 2 9 Du 545 5 0 3 9 2 52 50 6 4 6 2 6 0 5 8 5 6 5 4 5 2 4 8 3 7 2T 55 6 1 5 9 5 7 5 5 5 4 52 SEO 4 5 3 5 2 0 60 c Kok ee Reo dk e Ce he e eee 5 8 5 7 5 5 5 3 5 1 4 9 4 8 2 3 3 4 9 65 5 6 5 4 5 3 5 1 4 9 4 8 4 6 22 342 9 70
125. urvey departed from the basic LFS design in May 2003 5 1 Population Coverage The LFS is a monthly household survey of a sample of individuals who are representative of the civilian non institutionalised population 15 years of age or older in Canada s ten provinces Specifically excluded from the survey s coverage are residents of the Yukon Northwest Territories and Nunavut persons living on Indian Reserves full time members of the Canadian Armed Forces and inmates of institutions These groups together represent an exclusion of approximately 296 of the population aged 15 or over 5 2 Sample Design The LFS has undergone an extensive redesign culminating in the introduction of the new design at the end of 1994 The LFS sample is based upon a stratified multi stage design employing probability sampling at all stages of the design The design principles are the same for each province A diagram summarizing the design stages can be found in the document AppendixA LFS pdf 5 2 1 Primary Stratification Provinces are divided into economic regions ER and employment insurance economic regions EIER ERs are geographic areas of more or less homogeneous economic structure formed on the basis of federal provincial agreements They are relatively stable over time EIERs are also geographic areas and are roughly the same size and number as ERs but they do not share the same definitions Labour force estimates are produced for the EIERs for the us
126. value of the variable of interest by the final weight for each record then summing this quantity over all records of interest For example to obtain an estimate of the total number of weeks of employment insurance El received by women whose last absence was due to pregnancy multiply the value reported in question Q17B weeks received El by the final weight for the record then sum this value over all records with Q14 4 last absence due to pregnancy To obtain a weighted average of the form XIY the numerator x is calculated as for a quantitative estimate and the denominator f is calculated as for a categorical estimate For example to estimate the average number of weeks El was received by women whose last absence was due to pregnancy a estimate the total number of weeks x as described above b estimate the number of women Y in this category by summing the final weights of all records with Q14 4 then c divide estimate a by estimate b x Y 27 28 Residential Telephone Service Survey May 2003 User Guide 9 4 Guidelines for Statistical Analysis The Residential Telephone Service Survey is based upon a complex sample design with stratification multiple stages of selection and unequal probabilities of selection of respondents Using data from such complex surveys presents problems to analysts because the survey design and the selection probabilities affect the estimation and variance calculation proce
127. weighting for a supplement to the LFS Instead it is the sub weight which is used as explained in the following paragraphs 11 2 Weighting Procedures for the Residential Telephone Service Survey The principles behind the calculation of the weights for the Residential Telephone Service Survey are nearly identical to those for the LFS However this survey is a household weighted survey not a person weighted survey Also further adjustments are made to the LFS sub weights in order to derive a final weight for the individual records on the Residential Telephone Service Survey microdata file 1 An adjustment to account for the use of a five sixths sub sample instead of the full LFS sample 2 A province stratum adjustment to account for the additional non response to the supplementary survey i e non response to the Residential Telephone Service Survey for individuals who did respond to the LFS or for which previous month s LFS data was brought forward Note that a stratum roughly corresponds to an employment insurance economic region EIER economic region ER region as described in Section 5 2 2 Special Surveys Division Residential Telephone Service Survey May 2003 User Guide 3 The final adjustment ensured that estimates produced for a province household size group would agree with the known population totals for that province household size group The adjustments were made for household size groupings of 1 2 and 3 or more

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