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Microdata User Guide NATIONAL TENANT SATISFACTION SURVEY

1. KKK KKK KK KK KKK ckck ck ck ckckckckckckck KKK KKK KKK ck ck ck ck ck ck ck ck ckckckckckokck 010 UY 01 OY Y 00 ds P CO Q0 O1 CO 2900 0 O1 NO ds A oo od KKK KKK KKK KK ck ck ck ck ck ck ck ck ck ck ck ckckckckckckck ko kck KKK KKK KKK KK ck ck ck ck ck ck ck ckck ck ckckckckckckckck ko kk KKK KKK KK KKK ck ck ck ck ck ck ck ck ck ck ck ckckckckckckck kk ck KKK KKK KKK KK ck ck ck ck ck ck ck ck ck ck ck ckckckckckckck ko kck 10 0 123 0 87 0 71 0 61 5 55 0 50 2 46 5 43 5 41 0 38 59 31 58 21 9 24 6 22 55 8 5 3 4 9 7 2 3 0 7 1 2 5 0 6 20 1 9 18 17 L5 14 14 12 10 8 4 U UO Oo 4 3 KKK KKK KKK KK ck ck ck ck ck ckckckckckckckckckckckckckckckck ck KH ck ck KH A KH ok ESTIMATED PERCENTAGE 15 0 3 6 5 0 8 5 8 2 3 9 8 9 7 9 8 2 v9 8 9 4 3 8 0 8 5 9 0 3 9 9 2 0 Sos ok 8 oo OO 8 KKK KKK KKK KK ck ck ck KKK KKK KKK KKK KKK KKK ck ck ck ck ck ck ck ck ck ck ck ck ck KKK KKK KKK KKK KK ck ck ck ck ckckckckckckckckckckckckckckckckck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ko KKK KKK KKK KK ck ck ck ck ckckckckckckckckckckckckckckckckck ck ck ck ck ck ck ck ck ck ck ck ck ckck ck ckckckckckck 20 0 116 0 82 0 67 0 58 0 91 9 47 4 43 8 41
2. 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 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 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 In instances where due to technical or 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 Under no circumstances are unrounded estimates to be published or otherwise released by users Unrounded estimates imply greater precision than actually exists Sample Weighting Guidelines for Tabulation The sample design used for the National
3. Exclude 19 Furniture Furniture in workstation or support areas i e shared workspace for meetings storage printing copying reception etc including appropriateness of furniture adequate storage or work surface ergonomics effective and safe design of furniture condition of furniture state of repair inappropriate furniture inadequate storage or work surface ergonomics effective safe design of furniture broken or damaged furniture size of furniture need for new furniture modernization of furniture moveable partitions between workstations see 7 Office Privacy Noise 20 Accessibility Access and use of Access to special furniture or computer needs of building building by people with exterior walkways on for persons with disabilities see 19 OS disabilities including building property Furniture disabilities exterior walkways on drop off area and building property drop off parking facilities area and parking facilities entrances entrances elevators elevators stairs ramps washrooms stairs drinking fountains public ramps telephones tactile washrooms signage cafeterias drinking fountains lunchrooms and vending public telephones machines tactile signage cafeterias lunchrooms and vending machines in public common use areas 21 Other Everything not listed Everything not listed previously previously
4. SS Q04 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the task lighting 01 1 02 2 03 3 04 4 05 5 66 Does not apply to me SS Q05 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of overhead lighting 01 1 02 2 03 3 04 4 05 5 66 Does not apply to me Ne Go to SS Q07 DK RF Special Surveys Division 57 SS Q06 SS Q08 58 National Tenant Satisfaction Survey 2004 User Guide On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the overhead lighting oes not apply to me vUurom A On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of temperature too hot or too cold oes not apply to me pp Go to SS Q09 m cm A On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the temperature too hot or too cold 4 2 3 4 5 Does not apply to me On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfa
5. 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 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 estimate by the estimate itself and is expressed as a percentage of the estimate For example suppose that based upon the NTSS 2002 2003 survey results one estimates that 59 0 of individuals would like to see improvements made to their physical work environment and related services in their building and this estimate is found to have a standard error of 0 005 Then the coefficient of variation of the estimate is calculated as oe IE 100 0 8 0 590 There is more information on the calculation of coefficients of variation in Chapter 10 0 25 National Tenant Satisfact
6. 50 60 70 80 90 100 150 200 250 300 350 400 450 500 600 700 750 1 000 1 500 2 000 3 000 4 000 5 000 National Tenant Satisfaction Survey 2004 User Guide National Tenant Satisfaction Survey NTSS 2004 Approximate Sampling Variability Tables Quebec excluding National Capital Region ESTIMATED PERCENTAGE 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 DOR REF 80 9 80 5 79 3 77 2 75 0 72 8 70 4 68 1 65 6 63 0 54 5 44 6 dd REGE 57 2 56 9 56 1 54 6 53 0 51 4 49 8 48 1 46 4 44 6 40 7 31 5 a Ae 46 7 46 5 45 8 44 6 43 3 42 0 40 7 39 3 3459 36 4 33 2 2955 1 FI I I A ee 40 5 40 3 39 6 38 6 37 5 36 4 35 2 34 0 32 8 31 5 28 8 22 3 PA A 36 2 36 0 354 5 34 5 ub 325 31 5 30 4 29 9 28 2 25 7 9 9 RO 33 0 32 9 32 4 31 5 30 6 29 7 28 8 21 8 26 8 25 7 23 5 8 2 ne ESI Kok ER 30 4 30 0 29 2 28 3 2 4 3 26 6 25 24 8 23 8 21 1 6 8 DEREK OK ek Ok PRICK 20 5 28 0 27 3 26 5 25 7 24 9 24 1 VISA 224 3 20 3 5 8 BAER RIK RRB IRE RRS 26 8 26 4 25471 2940 24 3 2355 224 21 59 21 0 194 2 4 9 PATEAR E ese eon 2045 Zo 24 4 LS 2340 2259 21 4 5 20 7 19 9 18 2 4 1 a ee I I I I I 20 5 9 9 19 4 18 8 18 2 17 6 16 9 16 3 14 9 1 5 EK Koc OK IE EREEREER RT Kop T4 743 16 8 16 3 1548 19 2 14 7 14 1 12 9 0 0 BIE EGRE FIT A OK OK ok ek e eor T5359 5 4 1 540 14 6 14 13 6 1371 12 6 12 5 8 9 ERRE ER RAE EIR RAK oe eese EE 14 5 4 1 13 7 LS 12 9 12 4 12 0 11 5 10 5 8 1 REIKI EOROK SR Ck eK Ke EK KO AR EES AS 3 0 I23 125 3 1
7. Other Specify i scitu datu pastu echado Rind nennen Go to WS Q01S DK RF Go to WS Q02 How do you best describe your workspace 80 spaces How many years have you worked in this building Less than 1 year 1 to 2 years 3 to 5 years More than 5 years DK RF How long have you been in your current office Less than 1 year 1 to 2 years 3 to 5 years More than 5 years DK RF The answer in WS_Q03 should be less than or equal to the answer in WS_Q02 If not pop up hard edit with the following text Time spent in your current office is more than number of years working in the building this is incorrect Please correct value Would you like to see any improvements made to your physical work environment and related services in your building d daniela canes Go to WS_Q05 o O AO Go to SS_101 DK RF Special Surveys Division 55 National Tenant Satisfaction Survey 2004 User Guide Default Note WS QO05S Section SS I01 SS Q01 56 Which ones INTERVIEWER Mark all that apply Air Quality Temperature Office Size Layout Cleaning Office Areas Cleaning Washrooms Cleaning Common Use Areas Office Privacy Noise Lighting Natural Lighting Overhead Lighting Task Elevators Drinking Water Building System Noise Food Services Parking Building Security Shower Facilities Interior Finishes Furniture Accessibili
8. The following examples based on the NTSS 2002 2003 are included to assist users in applying the foregoing rules Please note that the data for these examples 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 Persons Possessing a Characteristic Aggregates Suppose that a user estimates that 33 396 employees were very satisfied with the services in their building 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 33 396 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 35 000 3 The coefficient of variation for an estimated aggregate is found by referring to the first non asterisk entry on that row namely 1 0 National Tenant Satisfaction Survey NTSS 2002 2003 Approximate Sampling Variability Tables for Canada NUMERATOR OF PERCENTAGE ESTIMATED PERCENTAGE 1 096 15 0 20 0 25 0 30 0 35 0 40 0 50 0 70 0 90 0 10 75 9 70 3 68 2 66 1 63 8 61 5 59 1 54 0 41 8 24 1 20 53 7 49 7 48 3 46 7 45 1 43 5 41 8 38 1 29 6 17 1 30 43 8 40 6 39 4 38 1 36 9 35 5 34 1 31 1 24 1 13 9 15000 reet emer 1 8 1 8 1 7 1 6 1 6 1 5 14 20000 rer mee 15 15 14 14 1 3 12 25000 rer eme Wr ARA 13 13 12 12 11 30000 rer en irn ARA AREA
9. 022 2 ze 2222 22 kkkkkkkk kkkkkkkk RA kkkkkkk 4 0 3 8 3 7 3 4 2 6 1800 kkkkkkkk delekdekdekeke Ree ze 22 22 27 kkkkkkkk kkkkkkkk RA kkkkkkk 3 9 3 7 3 6 3 3 2 5 1900 dekekdekdekek og kkkkkkkk RRR kkkkkkkk kkkkkkkk er kkk kk kkk 3 6 3 5 3 2 2 5 4500 kkkkkkkk og kkkkkkkk RRR kkkkkkkk Rok kkkkkkk kkkkkkkkid kkkkkkkk kkkkkkk kkkkkkkk kkkkkkkk 5000 kkkkkkkk kkkkkkkki kkkkkkkk kkk kkkk kkkkkkkk kkkkkkkk kkkkkkkk Rik kkkkkkkkid kkkkkkkk kkkkkkk kkkkkkkk kkkkkkkk 5500 kkkkkkkk kkkkkkkki kkkkkkkk kkk kkk k dekkdekdekek kkkkkkkk kkkkkkkk Rik kkkkkkkkd kkkkkkkk kkkkkkk kkkkkkkk kkkkkkkk NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION Special Surveys Division 37 National Tenant Satisfaction Survey 2004 User Guide 4 The figure at the intersection of the row and column used namely 3 8 is the coefficient of variation to be used 5 So the approximate coefficient of variation of the estimate is 3 8 The finding that 33 0 of employees in the Quebec Region who had worked in the same building for at least one year and felt that there were services which had deteriorated compared to one year ago can be published with no qualifications Example 3 Estimates of Differences Between Aggregates or Percentages Suppose that a user estimates that 49 337 83 622 59 0 of employees in the National Capital Region and Nunavut would like to see improvements to their physical work environment while 5 318 9
10. 10 1 1 explains the correct procedure to be used for ratios Region Acceptable CV Marginal CV Unacceptable CV 0 096 to 16 5 16 6 to 33 3 gt 33 3 Atlantic 200 over 50 to lt 200 under 50 Quebec excluding National Capital Region 230 amp over 60 to lt 230 under 60 National Capital Region and Nunavut 610 over 150 to lt 610 under 150 Ontario excluding National Capital Region 160 amp over 40 to lt 160 under 40 Western includes Northwest Territories 370 8 over 90 to lt 370 under 90 Pacific includes Yukon 110 over 30 to lt 110 under 30 Canada 510 8 over 130 to lt 510 under 130 Special Surveys Division 31 National Tenant Satisfaction Survey 2004 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 sample design This factor known as the design effect was determined by first calculating design effects for a wide
11. 12 1 1 1 1 1 0 35000 EEEE EEEE ARARARAR kkkkkkkkk RRR IK KEKE ERK kkk kkk 1 0 1 0 0 9 40000 kk kkk kk RRR kkk kk kkk kkkkk kk 0 9 0 9 45000 ARARARAR Ke RRR kkk kk kkk kkkkk kk 0 9 0 8 50000 kkk kkk kk kkkkkkkkk RRR kkk kkk kk kkk kk kk kkk kkkkk kk 0 8 55000 Fkk kkk kk RRR RRR IK KEK RRR kkk kk kkk kk kkk kk kkkkk kk 0 7 NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide 4 So the approximate coefficient of variation of the estimate is 1 0 The finding that there were 33 396 to be rounded according to the rounding guidelines in Section 9 1 employees who were very satisfied with the services in their building during the reference period is publishable with no qualifications Example 2 Estimates of Proportions or Percentages of Persons Possessing a Characteristic Suppose that the user estimates that 1 664 5 042 33 0 of employees in the Quebec Region who had worked in the same building for at least one year felt that there were services which had deteriorated compared to one year ago How does the user determine the coefficient of variation of this estimate 1 Refer to the coefficient of variation table for the QUEBEC REGION 2 Beca
12. 15 000 20 000 NOTE For correct usage of these tables 50 National Tenant Satisfaction Survey 2004 User Guide National Tenant Satisfaction Survey NTSS 2004 Approximate Sampling Variability Tables Canada 0 1 1 0 2 0 5 0 10 0 118 5 118 0 117 4 115 6 T42 5 83 8 83 4 83 0 9815 3 7945 68 4 68 1 67 8 66 7 64 9 59 3 59 0 58 7 57 8 56 2 239 0 52 8 024 9 ol 50 3 48 4 48 2 47 9 47 2 45 9 44 8 44 6 44 4 43 7 42 5 41 9 41 7 41 5 40 9 39 8 39 5 39353 3951 38 5 S745 3T 5 IIS 31 51 3655 35 6 ARTEN ES 30 5 3043 29 8 29 0 SAA 26 4 26 2 2548 2942 ERSPAREN 23 6 23 8 2371 22429 RAE EA EE 21 5 21 4 21 1 20 5 AA 19 9 19 8 19 5 19 0 RAR 18 7 18 6 18 3 17 8 dE 17 6 rs 17 2 16 8 RATEN 16 7 16 6 16 3 15 9 AE SE 15452 15 2 14 9 14 5 PERK 14 1 14 0 13 58 13 4 REDE RUE SK 13 6 13 6 135 3 13 0 FEAT 11 8 LIT 11 6 21 32 9 6 9 4 9 2 8 3 8 2 8 0 6 7 6 5 5 8 5 6 5 2 5 0 KARA ER k 4 6 KRETA ER k 4 3 eee Kok Ok kk kk Kok kk ek k k k ke k k k k RK 4 0 kk Ck kk Kok kk ko kk ko kk k k k ke ke k k k k ee E KKK KKK KKK KK ck ck ck ck ck ck ck ck ck ck ckckckckckckckck ko kck 3 Cn KKK KKK KK
13. 16 8 6 4 5 9 5 5 5 0 4 5 13 9 13 4 12 2 kk ckck ck ck ck ck ck ck ck ck ck ck ck ck ck oko ke ee 15 8 5 3 4 9 4 5 4 0 345 13 0 12 5 11 4 ok k A A Kok k koe ke ke ke EEE k 14 9 4 5 4 0 3 6 329 2 7 12 3 11 8 10 8 347 3 3 2 9 275 DET 11 7 11 2 10 2 2 5 2 158 1 4 1 0 10 6 10 52 9 3 1 6 3 0 9 0 6 0 2 9 8 9 5 8 6 1 2 0 9 0 6 0 2 9 9 9 5 9 1 8 3 9 4 91 8 9 8 6 8 2 7 9 7 2 3k ck kk ck ck kk kk kk RR RRR I I III III III III II ck ck ck ck 7 5 PIS 7 0 6 7 6 5 5 9 6 3 6 0 5 8 5 6 5 1 k ck kk ck kk kk kk kk Sk kk HH ck ck ck HH HH HH HH ck ck ck ck ck kock kc 4 8 4 6 4 2 FIR RK RRR RRR RI I III ck ke ck ck ck ck ck ck ck RR
14. 3 7 3 9 3 7 3 4 3 6 3 5 3 2 3 4 3 2 3 0 3 2 3 2 8 3 0 269 27 2 7 2 6 2 4 2 5 2 4 2 2 21 2 1 9 Special Surveys Division 70 0 O1 30 L2 hO CO UO OI AA OO PD 1 C CO XO QO UI OO UI OY O O1 O1 O QUI UO Oo HEHH HERET E MDO MD U GE BUD J O tio io O 90 0 N N CO Uds BHO DD I Oo O0OrPnNNoaydids UI JN EPEN C UI CO C0 Oy XO C0 OO 0d XO 01 CQ 2o C0 CO 1 OY UM National Tenant Satisfaction Survey 2004 User Guide 11 0 Weighting The final weights are based on the inverse of the initial probability that the telephone number was selected in the sample in addition to some adjustments The following steps were made to derive the final weight Step 1 The initial weight WEIGHT1 is calculated as WEIGHT Number of telephone numbers on the frame within the stratum Number of telephone numbers in the sample within the stratum For example if the frame contained 500 telephone numbers in a given stratum and was sampled at a rate of 20 100 telephone numbers would be selected In this example WEIGHT1 500 100 5 Every person in the sample in this stratum represents a total of 5 people in the population in this stratum Step 2 An adjustment to account for non response to the survey out of scope telephone numbers on the frame and the fact that some employees have more than one telephone number is calculated as dii gt the initial weights of all sample units gt the initial weights of
15. 669 55 0 of employees in the Western Region would like to see improvements to their physical work environment How does the user determine the coefficient of variation of the difference between these two estimates 1 Using the NATIONAL CAPITAL REGION AND NUNAVUT and the WESTERN REGION coefficient of variation tables in the same manner as described in Example 1 gives the CV of the estimate for employees in the National Capital Region and Nunavut as 0 6 and the CV of the estimate for employees in the Western Region as 1 1 National Tenant Satisfaction Survey NTSS 2002 2003 Approximate Sampling Variability Tables for National Capital Region and Nunavut NUMERATOR OF PERCENTAGE ESTIMATED PERCENTAGE 0 1 1 096 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 70 0 90 0 10 82 4 82 0 80 4 782 76 0 737 71 4 69 0 66 5 639 583 45 2 26 1 20 58 3 58 0 56 8 553 53 8 52 1 505 488 470 452 412 31 9 18 4 30 476 47 4 464 452 439 426 41 2 398 384 369 337 26 1 15 1 40 41 2 41 0 40 2 39 1 380 369 35 7 345 332 31 9 292 226 13 0 S5000 PARE TERKRKERE HARK EEE opponere CARRERA NE PEER ERER EKKERT donans HERREN 1 0 0 8 40000 A an RE III ooo EKINEN ado ERREKARI onec ARINAK FERRERS 0 9 07 45000 AO EENAA Deeper RER donne PIERRE REIHE EIER EA cas ERIC 07 5 50000 kkkkkkkk kkkkkkkk kkkkkkk kkkkkkkk kkkkkkkk kkkkkkk 2 2721272 272 kkkkkkkk dodo ug 2 21272 22 2 ze 22272 22 2 ze 2 222222 0 6 B5000 o e neon SRE REN 0 6 60000 Hart WE o Cd a
16. BSER QOS is nett eere 74 BSER Q00 need ttes 74 BSER QIO sacs nete ee 75 BSER Q11 sn ette 75 BSER A oboe ti 75 BSER 13 oi na ettet 75 BSER QI orrn a eene airon ees E EE NaN 76 BSER QIS co inienn re edt 76 BSER Q16 eheu er dete 76 BSER QI on ettet 76 BSER_O18 0 teet 77 BSER A nn 71 BSERQ029 3000 on Ata sits ade dei 72 BSEROOAS 0 0 73 BSERQO00S oe Rob Reve dir 74 BSERO098S u 820 ern 74 BSERQU S wn nip 75 C CASO meter 77 M MONEROl sonia 55 S SAO S ient eres 68 SALOON sintiendo ner 68 SAM QUO sies ied Peter er 68 SAL O03 siente d E eem 69 SA QO uisi nti em Rep 69 SA QOS Lise e ro iren RE 69 SA Q06 cerit reos ere ERE 69 SA QOJ iier tio ree reis 70 SA Q08 00m i sehr 70 SA QOO isse ae Tere ro ret RR 70 SA QIO iiie temere tis 70 SALOU Lait eret 71 SA QI aiti one tete tt 71 SEX QO 00 timeret 56 ST aiias tere eret ig 55 SL N06 i 56 SOMA iiam 55 E he 55 OO En aede 55 SOM ico 56 STI Q0 in 56 76 SE QOTA me inue 56 SI QUTS Gas eot ep 56 SOMO ii e teet ee ies 58 SS OO Lats ie Se ee ge esd 58 SS O02 em 59 SS a 59 99 O04 cir 59 SS Mid 59 O 0 em 60 SS OOD iuo ee dte det 60 SS DO em 60 SO ua 60 SS Q10 0 ne 61 SS QM incre Bann sn 61 NNUS 61 NNI 61 SS QL id 62 SS QT me 62 E 62 SS QL in tas san 62 SSCQIS ica ido 63 SS Oli its aces 63 SS O ont ir eer sans 63 A er oe 63 952022 0 pim dy 64 SS Innenseite 64 952024 A nitentem tons 64 9520029 sisi edid duin eed 64 95 026 d
17. CO 00 NUMERATOR OF PERCENTAGE 10 20 30 40 50 60 70 80 90 100 150 200 250 300 350 400 450 500 600 700 750 1 000 1 500 2 000 3 000 4 000 5 000 6 000 7 000 8 000 National Tenant Satisfaction Survey 2004 User Guide National Tenant Satisfaction Survey NTSS 2004 Approximate Sampling Variability Tables Western includes Northwest Territories ESTIMATED PERCENTAGE 0 1 1 0 2 0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 REFERAT 101 7 101 2 99 6 97 0 94 2 91 4 88 5 85 5 82 4 79 2 12 3 SEAR 7419 71 83 70 4 68 6 66 6 64 6 62 6 60 5 58 3 56 0 51 1 a Ae 58 7 58 4 SAS 56 0 54 4 52 8 SLs 49 4 47 6 45 7 41 7 RATEN 50 9 50 6 49 8 48 5 47 1 45 7 44 3 42 8 41 2 39 6 S6 GEO ACE ROUEN 4545 45 3 44 6 43 4 42 2 40 9 39 6 38 42 36 9 35 4 3243 ERAN 41 5 41 3 40 7 39 6 38 5 373 36 1 34 9 33 6 242 294 5 REE RE 38 4 38 2 Sd 36 7 35 6 34 6 39b KC 31 7 29 9 27 3 AER OR OK e 36 0 35 8 39 2 34 3 3 3253 31 3 30 2 29 1 28 0 25 6 e OK oR 335 9 33 7 33 2 32 3 31 4 30 5 29 5 28 5 21 5 26 4 24 1 a ORO Kok ok Ko eene 32 0 31 5 30 7 29 8 28 9 28 0 27 0 26 1 25 0 22 9 RR REAR KE AK IK RA 26 1 290 25 0 240 3 23 56 22 59 22 1 2153 20 4 18 7 EKER AAR IR KRACK KIER eoe KERR 2253 21 89 PARAN 20 4 94 8 Oo AL 18 4 ToT 16 2 EAE RARE EIR AE OK E Ke ek ek eae 19 9 9 4 8 8 843 Tez Fak 16 5 15 8 14 5 E HAE RIE RAE o ES 18 2 KS Dare 6 7 6 2 5 6 15 0 14 5 Il3 2 kk ckck ck ck ck ck ck ck ck ck ck ck ck ck ck kk RR RR
18. KH HH KKK KKK KKK KKK RK ck ckckckckckckckckckckckckckck ck KH KH ck KH KH ck ck KH HH ESTIMATED PERCENTAGE 15 0 62 44 36 31 2 255 23 22 20 19 16 14 125 Il 10 9 9 8 C oO 010 rn 10 LP 001 ioo nHn b 8 KKK KKK KK KKK ck ck ck ck ckckckck ck ckckckckckckckckckckckck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ok KKK KKK KKK KK ck ck ck ck ckckckckckckckckckckckckckckckckck ck ck ck ck ck ck ck ck ck ck ck ck ck ck a 20 0 60 42 34 30 27 24 22 21 20 19 154 13 124 ll 10 O0 OY O Oy I9 P2 EB O1 Oy PS IO oS Q0 JP X0 00 01 N KKK KKK KKK KKK ck ck ckckckckckckckckckckckckckckckckck HH HH HH HH ck ck ck ck ck ckck HH HH HH A kk 25 0 58 41 335 29 26 23 22 20 195 18 1 5 13 TI 1 0 9 J OO OO O 6 oO OY C JU J F2 P2 O1 O1 J N o N C 0 ds OS 8 KKK KKK KKK ck ck ck ck ck ck ckckckckckckckckckckckckck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckckckckckckckckck ck kck ck ck ck kc kc ko kk 30 0 56 40 92 28 25 23 21 20 18 17 14 12 Ll 10 9 S O100C0Qo i OOV GO C JO iO iQOO i I2 00 00 1 O OS O O J OO 00 10 35 0 54 38 Fla 2d 24 22 20 19 18 17 14 I2 10 10 9 54
19. KH HU 15 0 52 36 30 26 23 234 T9 18 I 16 13 Il 10 9 8 8 pA Q9 O0 Oi 4 4s O1 Ol 4S O1 J CQ C I2 ES OD KKK KKK KK KKK ck ck ck ck ckckckck ck ckckckckckckckckckckckck ck ck ck HH KH ck ck ck ck ck ck ck ck a 20 0 50 354 295 25 22 6 20 19 Tits 16 16 1 3 LL 10 94 co 00 6 NO OY O O I P2 C I2 O io WOOF J J Q ND 5 KKK KKK KKK KK ck ck ck ck ckckckckckckckckckckckckckckckck KH HH KH HH HH ck ck ck ck HH ck ck ckckckckckck A ck KKK KKK KKK KK ck ck ck ck ckckckckckckckckckckckckckckckck ck ck ck ck ck ck ck ck ck ck ck ck ckckck ck ckckckckckckckokck ESTIMATED PERCENTAGE 25 0 49 34 28 24 214 20 18 17 16 15 12 TIT 9 5s 0 CO XO C0 OO C0 O OO O J O1 Q0 C C1 O to O1 WO O1 Ov Oy J J CO to 7 30 0 47 334 2 234 21 19 17 16 15 15 12 10 25 SH LB 0 O UO O N CO OO OO xo WM ds Ud NN J 1 OO CO 5 KKK KKK KK KKK ck ck ck ck ckckckckckckckckckckckckck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckckckckckckckckckckckckck ck ck ck c
20. O1 JJOO NUMERATOR OF PERCENTAGE 10 20 30 40 50 60 70 80 90 100 150 200 250 300 350 400 450 500 600 700 750 1 000 1 500 2 000 3 000 NOTE For correct usage of these tables Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide National Tenant Satisfaction Survey NTSS 2004 Approximate Sampling Variability Tables Ontario excluding National Capital Region 0 1 1 0 ok ke ke ke 67 3 ok kk ke ke hy dock ke ke ke 38 9 KKKKKKK KKK ck ck ck ck ck ok kk kckckckckck ck ck ck ck ck ck ck ok KKKKKKK KKK ck ck ck KKK KKKKKKK ck ck ck ck k ck ck oko 67 47 38 33 5 30 2 25 oo e CUL I as e 3 kCkckckckckckckck ck ck ck ckck ck ck ck KK KK kc kk CkCkckckckckckck ck ck ck ck ck ckck ck ck KK kk KK CkCkckckckckckck ck ck ck ck ckck ck ck ck ckckckckckokck 17 REX OU ID UI p oy c oo 0 KKK KKK KKK KK ck ck ck ck ck ck ck ck ck ck ckckckckckckckck kc kk KKK KKK KKK ck ck ck ck ck ck ck ck ck ck ck ck ckckckckckckckck kk ck KKK KKK KKK KKK ck ck ck ck ck ck ckck ck ck ckckckckckckckckokck KKK KKK KK KKK ck ck ck ck ck ck ck ck ck ck ckckckckckckckck ko kck 10 0 64 45 374 32 28 26 24 22 23i 20 16 14 12 Ll 10 00 OY Q0 JUN TPP BD 9 KKK KKK KKK KK KKK KK KKK KKK KKK KK KH ck KH KH ck ck ck ck ck
21. RRA RRA RRA RR RR I I I ck kck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck k 3 6 KKK KKK KK KKK ckck ck ck ckckckckckckckckckckckckckckckckck ck ck ck ck ck ck ck ck ck ck ck ckckckckckckckckckckckckckckckckck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckck ck ck ckckckckckckckckckck ck ck ck ck ck ko kk KKK KKK KKK KK ck ck ck ck ckckckckckckckckckckckckckckckckck ck ck ck ck ck ck ck ck ck ck KK KKK KKK KKK KKK KKK KKK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckckckckckckckckckckck ck ck ko kk e e ja 914 42 BRD DIS 59 01 oO O P NM 5 3010 P MN QUO 0 MN OO Lis VO ODOASNSUSIDOOoWOUNDNDUWUMIU OOD N NO CO Hs BUD OY CO CO jo 6 3 KKK KKK KK KKK ck ck ck ck ckckckckckckckckckckckckckckckck HH KH HH HH ck ck ck ck ck ckckckckckckckckckckckckckckckckck HH HH HH HH ck ck ck ck ck ck ckckckckckckckckckckckckckckck ck ck HH ck ck ck ck ck ck ck ck KKK KKK KKK KKK KK ck ck ck ck ckckckckckckckckckckckckckckckckckckckck ck ck ck ck ck ck ck KK KKK KKK KKK KKK KKK KKK ck ck ck ck ck ck ck ck ck ck ck ck ck ckckckckckckckckckckckckckckck ck ck ck ck ck ck ck ck ck ck ck KKK NOTE For correct usage of these tables please refer to the microdata documentation 48 Special Surveys Division 90 0 PppPPPPPDNO oo FNw oo NM E32 BO CO 4 Oy OWOSNDSC0NDOS OO F2 O1 XO O1 DWDNDOoOPrMNDDND UN JU E p op pH p p N IN O0 OQ Q dS ss 0101010 I NUMERATOR OF PERCENTAGE 10 20 30 40 50 60 70
22. Survey 2004 User Guide survey design and the selection probabilities affect the estimation and variance calculation procedures 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 may 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 b
23. analysis will highlight areas which need improvement as well as areas where employees are satisfied with the standard of services delivered Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide 3 0 Objectives The main objectives of this survey were to e Determine tenant satisfaction in government buildings under the responsibility of Public Works and Government Services Canada PWGSC e Enable PWGSC to better understand and improve the needs of occupants in its buildings Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide 4 0 Concepts and Definitions This chapter outlines concepts and definitions of interest to the users Users are referred to Chapter 12 0 of this document for a copy of the actual survey questionnaire used 4 1 Survey Concepts The survey sample frame units are the telephone numbers of the target population The National Tenant Satisfaction Survey NTSS is a sample survey weighted to the number of tenants in the target population Population Federal Government of Canada employees who are in federal government departments or agencies participating in the National Tenant Satisfaction Survey and who are in buildings which have been identified by Public Works and Government Services Canada PWGSC as under their responsibility and in scope for the survey Target population Federal Government of Canada employees with telephone numbers who are in fed
24. and ensuring due diligence with respect to environmental and life safety systems compliance Closed office Room with four walls from floor to ceiling and with a door Special Surveys Division 13 National Tenant Satisfaction Survey 2004 User Guide 5 0 Survey Methodology The National Tenant Satisfaction Survey NTSS was administered between October 5 2004 and December 10 2004 to a sample of telephone numbers The NTSS design is briefly described in the sections below 5 1 Population Coverage The NTSS is a sample survey of federal government employees in buildings under the responsibility of Public Works and Government Services Canada PWGSC Specifically excluded from the survey s coverage are employees in buildings which were expected to have fewer than 100 federal government employees Also excluded were employees in federal government departments and agencies which chose not to participate in the survey These included Canada Border Services Agency Canada Revenue Agency Canadian Security Intelligence Service and Human Resources Development Canada Also excluded were buildings which PWGSC specifically chose to exclude for operational or other reasons and buildings for which it was not possible to obtain a list of employee telephone numbers 5 2 Sample Design For the 2004 survey PWGSC hired a private contractor to collect the telephone numbers from the telephone companies A new frame was created for this cycle of the sur
25. and must be used to derive meaningful estimates from the survey For example if the number of individuals working in a particular building is to be estimated it is done by selecting the records referring to those individuals in the sample that said they worked in that building and summing the weights entered on those records Details of the method used to calculate these weights are presented in Chapter 11 0 7 6 Suppression of Confidential Information Any estimates generated from this file for client use will be screened in order to protect the anonymity of individual survey respondents Answer categories are suppressed or collapsed into larger categories in order to ensure confidentiality Estimates generated will be released Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide to the user subject to meeting the guidelines for analysis and release outlined in Chapter 9 0 of this document It should be noted that the amount of information contained in the HTML documents differ in a number of important respects from the survey master files held by Statistics Canada As a result the totals on all tables may not always be equal These differences are the result of actions taken to protect the anonymity of individual survey respondents and or organizations Special Surveys Division 21 8 0 National Tenant Satisfaction Survey 2004 User Guide Data Quality 8 1 Response Rates The following t
26. estimated proportion of employees in the Quebec Region who had worked in the same building for at least one year and felt that there were services which had deteriorated compared to one year ago from Example 2 Section 10 1 1 would be calculated as follows X 33 0 or expressed as a proportion 0 330 t 2 a 3 8 0 038 expressed as a proportion is the coefficient of variation of this estimate as determined from the tables CI 0 330 2 0 330 0 038 0 330 2 0 330 0 038 CI 0 330 0 025 0 330 0 025 CI 0 305 0 355 With 95 confidence it can be said that between 30 5 and 35 5 of employees in the Quebec Region who had worked in the same building for at least one year felt that there were services which had deteriorated compared to one year ago 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 Let and X be sample estimates for two characteristics of interest Let the standard error on the difference x A be o X X If 1 is between 2 and 2 then no
27. importance is 5 00 But in reality 95 of respondents consider daycare facilities to be of such little importance that it does not apply to them So the average rating for importance of access to daycare facilities in the building would be more accurately shown as 0 05 Now let s examine the average satisfaction rating and why Does not apply to me is excluded from the calculation Let us say that these same 5 respondents with children of daycare age rated their satisfaction of the daycare facilities in their building with a 5 because they feel it meets all their needs The same 95 respondents who do not have children of daycare age responded with Does not apply to me If we were to rate these 95 responses with a value of 0 then the average satisfaction would be 0 05 But we know that the daycare facilities in this building are exceptional Therefore only those 5 respondents who responded and gave the daycare facilities a rating of 5 are considered in the average rating score 7 5 Weighting The principle behind estimation in a probability sample such as the NTSS 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 2 sample of the population each person in the sample represents 50 persons in the population The weighting phase is a step which calculates for each record what this number is This weight appears on the microdata file
28. number of people possessing a characteristic and it s CV value will be displayed in the lower portion of the left hand side of the window Rule2 Estimates of Proportions or Percentages of Persons 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 employees who would like to see improvements to their physical work environment is more reliable than the estimated number of employees who would like to see improvements to their physical work environment 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 proportion or percentage is based upon a subset of the total population e g those in their office for less than one year reference should be made to the proportion or Special Surveys Division Natio
29. o n oo KKKKK KKK KKKKK KKK KKKKK KKK KKK KKK KK ck kckck KKK 10 4 74 924 42 SU 33 30 28 oo WN Rito UN 1 KKKKKKK KKK ck ck ck KKK KKKKKKK ck ck ck KKK ck ckok KKKKKKK KKK ck ck ck KKK Coefficient of Variation Tables 13 52 42 36 33 30 21 26 24 23 oo OY P2 XO P O o AN 4 KKKKK KKK ck ck ck ck ck ck ck ck ck ckckckck ko kk KKKK KKK KKK ck ck ck ck ck ck ck ckckckck kc kk CkCkckckckckckck ck ck ck ck ck ckck ck ck ckckckckck kk KKK KKK KKK ck ck ck ck ckck ck ck ckckckck ko kk National Tenant Satisfaction Survey 2004 User Guide National Tenant Satisfaction Survey NTSS 2004 12 GQ CA OO CI Om ON Om Odds A oo ed KKK KKK KKK KK ck ck ck ck ck ck ck ck ck ckckckckckckckckck kk ck KKK KKK KKK KK ck ck ck ck ck ck ck ck ck ck ck ckckckckckckck kk ck KKK KKK KKK KK ck ck ck ck ck ckck ck ck ckckckckckckckckck ko kk KKK KKK KKK KK ck ck ck ck ck ck ck ck ck ck ck ckckckckckckck ko kck 10 0 70 50 40 35 31 28 26 25 23 22 18 L5 14 12 125 11 10 10 9 8 PROUNON O CQ 4S OY O J X0 Oy S XO O 00 5 KKK KKK KKK
30. of the estimate should be determined A rough estimate of the number of respondents for a particular cell in a table can be obtained by multiplying the total number of respondents as given in the appropriate column or row of the table by the percentage of the estimate given in the cell of interest If this number is less than 30 the weighted estimate should be considered to be of unacceptable quality Special Surveys Division 29 30 National Tenant Satisfaction Survey 2004 User Guide 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 Guidelines 1 Acceptable Estimates have a sample size of 30 or more and low coefficients of variation in the range of 0 0 to 16 5 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 6 to 33 3 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 esti
31. possible to identify lines used for facsimile machines data lines conference rooms etc All of these numbers were coded as out of scope Overall 31 of the telephone numbers on the frame were coded as out of scope for the survey This was higher than originally expected The out of scope rate affects the quality of the data by reducing the effective sample size Some allowance for the fact that telephone numbers would be out of scope was made when the initial sample sizes were calculated Some variables on the sampling frame play a critical role That is why at the time of the interview we confirmed with the respondent his location and department or agency 8 2 2 Data Collection Interviewer training consisted of reading the NTSS Interviewer s Manual attending a one day formal in class training session 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 In addition the computer assisted telephone interviewing system used for the collection reduced the possibility of error 8 2 3 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 interv
32. services in their building Their options are very satisfied somewhat satisfied somewhat dissatisfied and very dissatisfied A derived variable is created to calculate overall satisfaction which adds the very satisfied with the somewhat satisfied This derived variable is near the end of the Executive Summary HTML documents A final example of derived variables in the HTML documents is the Average ratings tables When calculating the average importance respondents who answered Does not apply to me were given a value of 0 So in this section the scale of importance ranges from 0 to 5 When calculating average satisfaction respondents who answered Does not apply to me were excluded from the calculation So in this section the scale of satisfaction ranges from 1 to 5 To illustrate the rationale for treating the Does not apply to me differently we will look at a fictional building In this fictional building there are 100 respondents 5 of whom have children of the age that could need daycare facilities For the importance question 95 respondents would probably rate their level of importance for access to daycare facilities as Does not apply to me While the remaining 5 respondents who have children of daycare age would rate their level of importance as 5 So if we were to exclude the Does not apply to me responses in calculating the average importance it would show that at the building level average
33. the Coefficient of Variation Tables for Categorical Estimates The following rules should enable the user to determine the approximate coefficients of variation from the 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 Special Surveys Division 33 34 National Tenant Satisfaction Survey 2004 User Guide Users who have access to the electronic version of the HTML tables also have the option of using an automated method of finding the CVs for estimates of the number and percentage of the surveyed population possessing a certain characteristic At the bottom of each table there is a link to a window which can be used to determine the CVs instead of looking in the Coefficient of Variation Tables provided in this guide Note that the CVs obtained with this method are also approximate and not official The CVs obtained using the tables and those obtained using the automated method may not always match exactly because when locating the numerator of the percentage in the approximate CV tables first column or the percentage across the top of the table if the exact values are not in the table the user must find the closest values and find the CV for those values In the automated method the percentage and the exact value of the population value are used in a formula The automated method also has an op
34. who would like to see improvements to their physical work environment or the proportion of employees who are very satisfied with the services in their building 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 Would you like to see any improvements made to your physical work environment and related services in your building R Yes No Q Overall how satisfied are you with the services in your building R Very satisfied Somewhat satisfied Somewhat dissatisfied Very dissatisfied 9 3 1 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 E b summing the final weights of records having the characteristic of interest for the denominator then C dividing estimate a by estimate b X 17 9 4 Guidelines for Statistical Analysis The NTSS is based upon a stratified sample design with simple random sampling within strata Using data from such complex surveys presents problems to analysts because the Special Surveys Division National Tenant Satisfaction
35. your level of satisfaction with their responsiveness 1 2 3 4 5 Does not apply to me On a scale of 1 to 5 where 1 is lowest and 5 is highest please rate your satisfaction with the following aspects from the property management team your level of satisfaction with their knowledge 1 2 3 4 5 Does not apply to me On a scale of 1 to 5 where 1 is lowest and 5 is highest please rate your satisfaction with the following aspects from the property management team your level of satisfaction with their courteousness 1 2 3 4 5 Does not apply to me On a scale of 1 to 5 where 1 is lowest and 5 is highest please rate your satisfaction with the following aspects from the property management team your level of satisfaction with their communication skills OODD Does not apply to me DK RF Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide BSER_Q18 Overall how satisfied are you with the level of Project Management services received from PWGSC s team INTERVIEWER Read categories to respondent Very satisfied Somewhat satisfied Somewhat dissatisfied Very dissatisfied DK RF ROND CAI_SO END OF INTERVIEW Special Surveys Division 75 National Tenant Satisfaction Survey 2004 User Guide INDEX B BSER QO se ee seen 71 BSER QO02 anal 72 BSER 003 nee tre 72 BSER 004 222 ee 73 BSER QO5 nnt trae 73 BSER Q06 5 nere ee tes 74 BSER QUJ en 74
36. 0 38 7 36 7 2959 25 9 23 2 21 2 19 6 18 3 IT 2 3 16 4 0 9 4 6 5 2 7 8 2 7 4 1 9 7 3 0 25 0 112 TO 64 56 20 45 42 39 STi 35 29 254 224 20 19 TT 16 15 14 l3 13 Ils wo ED I GY ol ON SS MAG DO uS O1 O0 OO MH OO On BAT BONN 00 SB CO ho M2 Q0 CJ Q0 S ds ds 01 01 0 J 30 0 108 76 62 54 48 44 38 36 34 28 IB 00 HP Hs Oy O0 HIS Po 49 C0 1 O OO U1 OOWMND NND CO CO 1 COO CO PO S O UNO 0 N N CO CO CO CO 4S ds S 01 OY J1 OO OO MN UO 4 OUI Oy IAW please refer to the microdata documentation 35 0 40 0 50 0 104 6 100 5 91 7 733 9 7140 64 8 60 4 58 0 5249 52 3 50 2 45 8 46 8 44 9 41 0 42 7 41 0 37 4 39 5 38 0 34 7 37 0 35 5 32 4 34 9 33 5 30 6 33 1 31 58 29 0 27 0 25 9 23 7 23 4 22 5 20 5 20 9 20 1 8 3 9 1 8 3 6 7 dsd 7 0 3 9 6 5 5 9 4 5 5 6 50 344 4 8 4 2 3 0 au 3 0 1 48 2 5 2 0 1 0 2 1 1 6 0 6 0 5 0 0 9 2 8 5 8 2 Tm 7 4 HET 6 5 6 0 5 8 5 3 5 2 5 0 4 6 4 7 4 5 4 4 3 4 1 3 7 4 0 3 88 3 5 37 3 6 3 2 3 5 3553 ED 3 3 3 2 2 9 3 0 2 8 2 6 2 7 2 6 2 4 2 3 2 2 Li Special Surveys Division 70 0 DWONABAOATONARFOADAHFTNUNDOANDONWOWUATF Om SS BuO RPNDNNNDNNOOUY 4 O1 O1 CO 90 0 NNN Q HP HP P HIP HP P P P N N PMN o ds 4S 4S 0101 0101073010 O UY CQ 4S O1 OY OO OO Q OF XO P2 NO CO S GS 01 OO HIPS 4 40 CO F2 XO C COO P2 O1 iO O1 o 0 OY O OI OI 1 C
37. 149 11 5 TII 10 7 9 7 7 5 FERIA KAR RK A AHR RAH ROR AIR FARE e enses 2 2 11 9 1155 IX 10 8 10 4 10 0 9 1 7 0 5 112 10 8 10 5 10 1 9 8 9 4 8 6 6 6 kckckckckckck ck ckckckckckckck ck ckckck ck ckckokokckckok ck A A 0 9 10 6 10 3 10 0 9 6 9 3 8 9 8 1 6 3 0 0 9 7 9 4 9 8 8 8 5 8 1 7 4 5 8 9 0 8 7 8 4 8 1 7 8 7 5 6 9 Be 8 7 8 4 8 7 9 7 6 7 3 6 6 5 FIR RRR RRR I I III III III III Kk had 7 0 6 8 6 6 6 3 5 8 4 5 3k kk kc kk kk KR RRR RI I ok ke ke ck ck ko ck ck ck ck ck ck ckck ck ckck ck ck ck ck ck ck ck kk 5 8 5 6 5 4 5 1 4 7 3 6 4 6 4 5 4 1 3 2 FI RRR RRR I I I II III I III III III RR RR RR I I I I I III I III III III ck ck ck ck ck ck k 3 3 2 6 ok
38. 80 90 100 150 200 250 300 350 400 450 500 600 700 750 1 000 1 500 2 000 NOTE For correct usage of these tables National Tenant Satisfaction Survey 2004 User Guide National Tenant Satisfaction Survey NTSS 2004 Approximate Sampling Variability Tables Pacific includes Yukon 0 13 1 0 2 0 ICO 56 3 56 1 ICO 39 8 39 6 IG 32 5 32 4 28 0 2533 22 9 KKK KKK KKK ck ck ck ckck ck ck ck ckckckck kc kk CkCkckckckckckck ck ck ck ck ck ck ck ck ck ckckckckckckck CkCkckckckckckckckck ck ck ck ck ck ck ck ckckckckckckck CkCkckckckckckck ck ck ck ck ck ck ck ck ck ckckckckckckck 14 dis 0 t0 O1 J O io ON oo 3 KKK KKK KKK KK ck ck ck ck ck ck ck ck ck ck ckckckckckckckck ko kk KKK KKK KKK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckckckckck kk ck KKK KKK KKK KKK ck ck ck ck ck ck ckck ck ck ckckckckckckck ko kk np o o 93 38 31 26 24 243 5 20 19 1 7 IF 13 125 10 9 jo SER 5 XD oC QU ID CO X0 DDR 8 KKK KKK KK KKK ck ck ck ck ck ckckckckckckckckckckckckck ck ckck ck ck ck ck ck KH KH ok KKK KKK KK KKK ck ck ck ck ck ckck ck ckckckckckckckckckck ck ck ck ck ck ck ck ck
39. 80 Special Surveys Division
40. AM MES location of parking availability of bike racks cost of parking maintenance of parking areas snow removal etc 16 sieh Be dad of control of entrances by demeanor of security personnel ecurity people and their uards and securit belongings in the building puce systems y control of entrances by e guards and security o coridor access systems dark unoccupied space corridors unoccupied after hours building space after hours access building access 17 Eee Shower facilities T availability of showers washroom facilities see 5 seien men e no showersornot Cleaning Wastrooms number of showers enough Showers cleaning and condition of cleaning of showers showers condition of shower facilities repairs to shower facilities 18 ein He of worn torn frayed furniture repairs see 19 Furniture inishes ase building finishes including flooring e g carpet tile linoleum wall treatments coverings e g paint wallpaper ceiling finishes e g tiles paint window coverings e g blinds curtains solar film carpets chipped cracked flooring e g tiles or linoleum chipped peeling paint peeling torn wallpaper chipped cracked broken plaster or drywall broken soiled ceiling tiles broken blinds shades curtain hardware torn stained curtains peeling solar film on windows Special Surveys Division 79 Description Include
41. K KK ck ck ck ck ck KKK ck ckckckckckckckckck ck KH KH ck ck ck ck ckck HU KKK KKK KKK KK ck ck ck ck ckckckck KKK KKK KKK KKK ck ck ck ck ck KH KH HH KKK KKK KK KKK ck ck ck ck ckckck ck ckckckckckckckckckck ck ckck ck ck ck ck ck ck ck ck ck ck KKK ESTIMATED PERCENTAGE 15 0 109 Fra 63 54 48 44 41 38 36 34 28 24 3 3 1 T 9 6 3 6 4 6 2 4 9 0 5 3 3 15 5 1 1 6 9 9 7 3 5 9 5 1 9 6 5 1 8 20 0 106 15 61 93 47 43 40 34 395 334 2d 23 214 o 0 0 2 0 4 3 1 5 3 5 4 E 2 4 9 8 8 0 7 7 2 6 7 5 1 3 7 3 0 7 5 4 0 7 4 ho R2 CO C0 CO CO iS ds uS 01 0 1 O0 OO IN IN 0 O1 O1 O I 25 0 W to hO 45 O tO N O P2 OL S Yi Y C O1 YN BAN UI O UI UN WO tio io C C o N NN UY UY UY CO ss 0101 2 O0 CO IS I2 00 4S OD I 30 0 NDOY0OOo r2 C001 12O i OO JOR 00000 1200 2 OO 0 OY S EB E O1 O1 4S Oy WE DN N NN Q0 CO CO Ys ds 01 O1 J OO iO r2 EO D SP BU OS please refer to the microdata documentation 35 0 40 0 50 0 95 6 91 8 83 8 67 6 64 9 59 3 5542 53 0 48 4 47 8 45 9 41 9 42 8 41 1 37 5 39 0 IO 34 2 36 1 34 7 31 7 33 8 32 5 29 6 3179 30 6 2 9 30 2 29 0 26 5 24 7 Ziel 21 6 21 4 20 5 8 7 9d 8 4 6 8 7 5 6 8 dl 6 2 S45 4 2 5 1 4 5 3 3 4 3 347 2 5 3 5 3 0 9 253 1 89 0 8 1 4 1 0 0 0 1 0 0 6 9 7 9 6 9 2 8 4 7 8 ISD 6 8 6 8 6 5 5 9 5 5 5 3 4 8 4 8 4 6 4 2 4 3 4
42. KK KKK KKK KK ck ck ck ck ckckck ck ckckckckckckckckckckckckck KKK KKK ck ck ck ck ck KKK KKK KKK KKK KKK KKK KKK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckock ck ckckckckckckck 50 0 HHHHHRHHNDNDNDw wu CORWDAINDAORPWHAOIN 34 ZU Q0 F2 CO OO O1 tO CQ tO O O1 OO O J Oy OY iO O1 Oy S MW J C 0103 O0 Oy J 1 00 CO 0 KKK KKK KKK KKK ck ck ck ckckckckckckckckckckckckckckckckckckckckck ck ck ck ck ck ck KKK KKK KKK KKK KKK KKK ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckckckckckckckckckck ck ck k ck ko kk KKK KKK KKK KK ck ck ck ck ckckckckckckckckckckckckckckckckck ck ck ck ck ck ck ck ck ck ck ck ckckckckckckckckckckckckckckckckck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ck ckckckckckckckckckckck KK KH ko k ck kk KKK KKK KK KKK ck ck ck ck ckckckckckckckckckckckckckckckckck ck ck ck ck ck ck ck ck ck ck ck ckckckckckckckckckckckckckckckckck ck ck ck ck ck ck ck ck ck ck ck ck ck ck KKK ck ckckckckckckckckckck ck ck ck ck ck ck ck ck ck ck ck ok ok please refer to the microdata documentation Special Surveys Division 70 0 NNN 0 8 3 0 8 6 5 4 3 2 0 9 8 T 6 6 6 5 5 4 4 4 3 2 2 2 1 O0 O 4 XO C F2 XO C0 OO L2 O1 XO UNF UO DA ds C0 4S DO WO xe 90 0 PRPRPEREN CORWAW Q p NoGR Xo O0 CO C UI 1 O C 1 C F2 O1 iO CO iO OY O1 OO OY 1 Ov HP HP pP Hn P mPnr M PS PS O0 Q Q CQ 0 ds BB USD J J OO NUMERATOR OF PERCENTAGE 10 20 30 40
43. KK ck ck ck ck ck ckckck ck ckckckckckckckckck ck ckck ck ck ck ck kc ko kk KKK KKK KK KK KK ck ck ck ckck ckckckckckckckckckckckck ck ckck ck ck ck ck ck kk ok 15 0 68 48 39 34 30 28 26 24 22 23 Likes 15 13 172 11 LO 10 XO N 10 J CO XO 0 0 OO Hs CO JJ XO C0 OF O0 BP Oy CO Mo 20 0 66 47 38 33 29 27 25 234 22 21 17 14 13 12 Lla 10 9 OO ow 6 O O5 io OU Q ho C iO PO r2 PO OY IO 2 Oo BUD I KKK KKK KKK KK ck ck ck ck ckckckckckckckckckckckckckckckck ck ck ck ck ck ck ck ck ck ck ck ck ckckck ck ckckckckckckckckck ESTIMATED PERCENTAGE 25 0 64 6 45 7 34 2 32 3 28 9 26 4 24 4 22 8 21 5 20 4 16 7 14 4 1299 118 10 9 10 2 9 6 9 8 3 7 7 7 5 6 5 Ba KKK KKK KK KK ck ck ck ck ck ckckckckckckckckckckckckck ck HH HH HH HH HH ck ck ck ck ck ckckckckckckckckckck ck KH ck ck ck KH KH A KH ok 30 0 62 44 36 31 21 25 23 224 20 19 16 14 12 11 10 4 P2 NDNDuHroweveu iU cor rn 10 rP00U0 io F0 O Hm P eA CO Ov J OO OO wo Approximate Sampling Variability Tables Atlantic 35 0 60 42 34 30 26 24 22 215 20 l9 15 13 12 ll 10 4 WO ON OO GT MO OE OD wT Oo PR JAR Hs 010 30 tio w 40 0 bee pde ON NND Gas Ot O O m hh 4 0 t0 O P yu c WON gt OO J XO OU h2 O F2 OO UO Oy XO XO CO CO 0 Oy OO WO 4 to CO BU 01 OF 00 OW p K
44. Microdata User Guide NATIONAL TENANT SATISFACTION SURVEY 2004 La E eus Canada National Tenant Satisfaction Survey 2004 User Guide Table of Contents 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 INTFOUCHON com E indonesia nadaa 5 Bac o ee 7 ODjCCUVES Ce 9 Concepts andiDefinitionms e a eae deals 11 4 1 survey COncepts nee a etie Rr Ce dt 11 4 1 1 Participating Departments and AgencieSs RN 12 4 2 Survey Definitio NS eiei d rii pee trei nn read 13 Survey Methodology 2 2 zu Kaas a ee LIO 15 5 1 Population Coverage 15 5 2 sample Design 3t te eo d eh ee ied ee ota ab da ott etes 15 5 2 1 StratifiCatiOn tut irit pd rere e Pt feet fea Peta iratus 15 5 2 2 Sample Allocation and Selection nn 15 Data Collection mee ER 17 6 1 Questionnaire Design and Testing nnne 17 6 2 INTOSTVISWINO pto 17 6 3 Supervision and CONtrol entrent nnne enn 17 6 4 Non response to the National Tenant Satisfaction Survey pp 17 Data ProCe S SING mn 19 7 1 BEICWerTUm A TL ERREUR 19 7 2 Eding ien i tL HAE SI Ne cec NE O 19 7 3 Coding of Questionnaire Information 0 19 7 4 Creation of Derived Variables nn 19 7 5 IO 20 7 6 Suppression of Confidential Information pe 20 Data Quality a is 23 8 1 Response R OS aenea iiaei ee ae na nn 23 8 2 S rVey ErITOES o iiaii i eiad ai a ud va a deudas 23 A Frame e EE 23 9 2 2 Data Collection ns ed 24 8 2 3 Non fesponse r nunna A ehe ee 24 8 2 4 Measurem
45. Tenant Satisfaction Survey NTSS was not self weighting When producing simple estimates including the production of ordinary statistical tables users must apply the proper sampling weight Special Surveys Division 27 National Tenant Satisfaction Survey 2004 User Guide 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 Data on the proportions and average values of the HTML tables are weighted estimates The population represents the weighted number of people excluding those who refused or didn t know the answer for each question The number of respondents represent the number of people who answered these questions excluding refusals and don t knows 9 3 Categorical Estimates Before discussing how the NTSS data can be tabulated and analysed it is useful to describe the type of point estimate of population characteristics which can be generated from the data file for the NTSS 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 employees
46. WOOATRFPFANDWONFWNWDW BW OID OD NN I CO CO 5 40 0 52 Ss 30 26 23 214 19 18 17 16 13 TEs 10 5 OY O0 O I CO CO F3 Q0 OO 4 OO C0 iO Oy O1 J UI Oy O1 Oi OO ds BN WE BD N KKK KKK KKK KK AAA ckckckckckckckckckckckckckckckckck HH KH HH HH HH HH ck ckckckckckckckckckckckckckckckck ck ck ck ck ck ck ck ck ck ck ck ck HH ck ck ck ck ck ck HH HH HH RK 50 0 PRPRPRPRENNNWSEA CONUADWAVOFPWIWA 3 ou swbdoHhroahroakrkHovcHhrukP0o OO 0 HS 01 01010 J 4 CO 9 KKK KKK KKK KK ck ck ck ck ckckckckckckckckckckckckckckckckck ck HH KKK ck ck ck ck HH HH HH HH HH KH HH HH HH HH HH HH ck ck ck ck ck ck HH KH HH HH HK HK KK HH KH KH ck ck ck ck ck ck ck KKK please refer to the microdata documentation 47 e e N 9 6 37 26 21 18 16 Tos 14 13 12 13 9 O0 JU ius O0 ho OU XO YO 4S COO Jas E OO EB OY O1 4S IND ES 8 7 6 6 5 5 5 4 4 4 3 3 2 o 90 0 FS CONOR NO 1rP 000009 P249 OY OCGO OO U1 CO I or 1 Oy BEHEA L2 p prx PKS MN PS U C C C C ds BOD II
47. a file that is held by Statistics Canada 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 transmitted over a secure line to Ottawa for further processing 7 2 Editing A series of edits were performed on the capture file to check the data paths and flows and for internal consistency 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 Questionnaire Information During the interview respondents were asked to confirm the building location and department or agency where the telephone number belonged Information related to the department or agency was captured and coded at the time of the interview Building name an
48. able summarizes the response rates to the National Tenant Satisfaction Survey NTSS by region Number of Sample Eligible Number of Response Size Telephone Respondents Rate Numbers Atlantic 2 417 1 813 1 344 Quebec excluding National Capital Region 2 300 1 303 1 091 National Capital Region and Nunavut 9 440 6 866 5 289 Region Western includes Northwest Territories 2 265 1 532 1 227 Pacific includes Yukon 1 803 1 113 870 8 2 Survey Errors 74 1 83 7 mo Ontario excluding National Capital Region 949 807 0 782 70 The estimates derived from this survey are based on a sample of telephone numbers 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 occurr
49. acement see Size Layout dadas aa arrangement or 19 Furniture a es er a configuration of ergonomics of furniture see 19 ee f r meetings workstations partitions Furniture storage printing copying and furniture size of desk surface see 19 reception etc Includes workstations and support Furniture arrangement configuration areas too small or too inadequate furniture see 19 of workstations and crowed Furniture furniture size of proximity to co not enough file cabinets see 19 workstations and support workers team members Furniture en of aesthetics of office design 4 Cleaning Cleaning of individual spot cleaning washing of cleaning of desks and computer Office Areas offices workstations and support areas i e shared workspace for meetings storage printing copying reception etc Cleaning includes washing of wall and floor surfaces dusting vacuuming garbage removal recycling Special Surveys Division walls and floors dusting vacuuming garbage removal emptying of recycling bins screens in offices workstations cleaning of appliances microwaves refrigerators in support area 77 Description Include Exclude 5 ng E pipi ee cleaning of toilets sinks inadequacy of washroom facilities mide di fa E do als floors walls mirrors condition age of washroom fixtures mirrors replacement of _ e Mad washroom moderniz
50. apital Region and Nunavut 9 440 Ontario excluding National Capital Region 1 788 Western includes Northwest Territories 2 265 Pacific includes Yukon 1 803 Canada 20 013 Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide 6 0 Data Collection Data collection for the National Tenant Satisfaction Survey NTSS was carried out from October 5 2004 to December 10 2004 Interviews were conducted over the telephone from the Statistics Canada regional office in Sturgeon Falls 6 1 Questionnaire Design and Testing Qualitative testing in the form of focus groups was used to test and evaluate the questionnaire and survey concepts During March and April of 2001 seven focus group sessions took place in the National Capital Region in both official languages each lasting two hours Before they took part in the focus groups tenant participants were contacted by telephone to complete the survey This was done in order to get their reactions from a respondent s point of view The main objectives of the focus groups were 1 To test the overall reaction of knowledgeable clients Client Service Unit Directors landlords and building tenants 2 To test the appropriateness and applicability of concepts content and flow 3 To test the response burden and respondent friendliness 4 To test the cognitive processes of building tenants in responding to the questionnaire including an assessment of th
51. ation soap toilet paper and Lm ang paper poor ventilation see 1 Air Quality paper towels removal of garbage removal of garbage odours related to cleaning or lack of cleaning cleaning products 6 Cleaning Cleaning of common use e cleaning of wall and floor cleaning of office workstations or nn areas such as lobbies surfaces support areas see 4 Cleaning Use Areas DK yi aa dusting Office Areas cafeterias Cleaning vacuuming includes washing of wall garbage removal and floor surfaces cleaning products dusting vacuuming garbage removal 7 Office Privacy and noise levels e no partitions noise from building mechanical ur u a de no area for private systems see 13 Building System office loc i e floor mesures or ppone cals em to ceiling partitions open soundproofing concept availability of noise from photocopiers private meeting phone call printers surrounding area soundproofing work activities noise from photocopiers need for walls or door printers 8 Lighting Natural light coming not enough natural light artificial lighting overhead and task Natural e ae or ho windows lighting see Lighting 9 l glare from natural light Overhead or 10 Task coming through windows or skylights sun 9 d x Overhead or area lighting e too dark natural lighting from windows see offices workstations glare support areas and flickering common use areas 10 ng E Special li
52. conclusion about the difference between the O d 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 Special Surveys Division Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide 10 3 1 Example of Using the Coefficient of Variation Tables to Do a T test Let us suppose that the user wishes to test at 5 level of significance the hypothesis that there is no difference between the proportion of employees in the National Capital Region and Nunavut who would like to see improvements to their physical work environment and the proportion of employees in the Western Region who would like to see improvements to their physical work environment From Example 3 Section 10 1 1 the standard error of the difference between these two estimates was found to be 0 0070 Hence X X _0 590 0 550 _ 0 040 _ c 0 0070 0 0070 d t 5 71 Since 1 5 71 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 43 NUMERATOR OF PERCENTAGE 10 20 30 40 50 60 70 80 90 100 150 200 250 300 350 400 450 500 600 700 750 1 000 1 500 2 000 3 000 4 000 5 000 6 000 NOTE For correct usage of these tables 44
53. ction how would you rate the importance of air quality OPOD Does not apply to Me Go to SS Q11 DK RF Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide SS Q10 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the air quality 01 1 02 2 03 3 04 4 05 5 66 Does not apply to me DK SS Q11 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of parking availability 01 1 02 2 03 3 04 4 05 5 66 Does not apply to Me nen Go to SS Q13 DK RF SS Q12 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the parking availability 01 1 02 2 03 3 04 4 05 5 66 Does not apply to me SS Q13 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of outside lighting 01 1 02 2 03 3 04 4 05 5 66 Does not apply to Me nnne Go to SS Q15 DK RF Special Surveys Division 59 SS Q14 60 National Tenant Satisfaction Survey 2004 User Guide On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would
54. d or address related to the location of the respondent was also recorded by the interviewer and then used to code his her location to a specific building code A small number of data items on the questionnaire were recoded These data items were related to additional services important to tenants such as office space food services privacy drinking water and shower facilities Using automated coding techniques and manual verification many of these open ended responses were recoded into existing categories on the questionnaire 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 and tabulations For example SS Q01 asks on a scale of 1 to 5 where 1 is lowest importance and 5 is highest importance how the respondent would rate the importance of natural lighting while SS Q0 asks on a scale of 1 to 5 where 1 is lowest satisfaction and 5 is highest satisfaction how the respondent would rate his her level of satisfaction with the natural lighting A derived variable was created and included in the HTML document to show the average score of importance of natural lighting and the average satisfaction with the natural lighting Special Surveys Division 19 20 National Tenant Satisfaction Survey 2004 User Guide Another example would be question BSER_Q05 which asks for the respondents overall satisfaction with the
55. e respondents understanding of various concepts and content and an evaluation of the respondents ability to respond to questions 6 2 Interviewing Statistics Canada interviewers are employees hired and trained to carry out surveys Interviewers contacted each of the sampled telephone numbers to conduct the interview Data was collected using a computer assisted telephone interviewing CATI system Interviews lasted 10 minutes on average 6 3 Supervision and Control All NTSS 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 survey and also for periodically monitoring their interviewers and reviewing their completed documents 6 4 Non response to the National Tenant Satisfaction Survey In total 13 803 telephone numbers were eligible for the survey the NTSS interview was completed for 10 770 of these telephone numbers for a collection response rate of 78 More detailed information on response rates is presented in Chapter 8 0 Data Quality Special Surveys Division 17 National Tenant Satisfaction Survey 2004 User Guide 7 0 Data Processing An output of the National Tenant Satisfaction Survey NTSS is a clean microdata file This chapter presents a brief summary of the processing steps involved in producing this file The main output is the HTML documents that were derived from the microdat
56. e standard error of a difference d X X is O a where X is estimate 1 National Capital Region and Nunavut X is estimate 2 Western Region and and are the coefficients of variation of X and X respectively That is the standard error of the difference d 0 590 0 550 0 040 is o 0 590 0 006 0 550 0 011 0 00001253 0 00003660 0 0070 3 The coefficient of variation of d is given by ac d 0 0070 0 040 0 175 4 So the approximate coefficient of variation of the difference between the estimates is 17 5 The difference between the estimates is considered marginal and Statistics Canada recommends this estimate be flagged with the letter M or some similar identifier and be accompanied by a warning to caution subsequent users about the high levels of error associated with the estimate Special Surveys Division 39 40 National Tenant Satisfaction Survey 2004 User Guide Example 4 Estimates of Ratios Suppose that the user estimates that 5 318 employees in the Western Region would like to see improvements to their physical work environment while 49 337 employees in the National Capital Region and Nunavut would like to see improvements to their physical work environment The user is interested in comparing the estimate of Western Region employees versus that of the National Capital Region and Nunavut employees in the form of a ratio How does the user deter
57. eger door SHE dol FREER hobbit dani JOGOO Exeter SAREE REE A O a KARMAN e O SEREERER ds cape ode NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide National Tenant Satisfaction Survey NTSS 2002 2003 Approximate Sampling Variability Tables for Western NUMERATOR OF PERCENTAGE ESTIMATED PERCENTAGE 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 10 Wr 459 45 7 450 438 426 41 3 400 386 372 358 32 7 253 14 6 20 Wer 325 32 3 318 310 30 1 292 283 273 263 253 231 179 10 3 30 mr 265 264 260 253 246 238 231 223 215 20 7 189 14 6 8 4 40 230 229 225 219 213 20 7 200 193 186 179 163 12 6 7 3 50 205 204 20 1 196 190 185 179 173 166 160 146 11 3 6 5 60 18 8 18 7 184 179 174 169 163 158 152 146 133 10 3 6 0 70 Ye 174 173 170 166 161 156 151 146 141 135 12 3 9 6 5 5 ii RER RRERRE ER ERSTER EREERE VE RERRRE SNEEKER CEEEEEEER SERRE EE 1 5 1 2 0 7 A RER aree RR coiere HRA ERERREER ER EHRE gno ann 1 1 0 7 5500 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkk RAR kkkkkkk kkkkkkkk kkkkkkk RARA ARMAR ARA kk 1 El 0 6 6000 PEREA SOR HER IIR IIE E OE E dd O bo 1 0 0 6 6500 Fra AE Me o ERIE TA ORES fc RI KAKEN KIE PEO RAI 1 0 0 6 7000 re ra re A RI RERAEREE IERKERERE EERRERER 0 6 NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION 2 Using Rule 3 th
58. ements to their physical work environment is 5 318 49 337 which is 0 11 1 to be rounded according to the rounding guidelines in Section 9 1 The coefficient of variation of this estimate is 1 3 which is releasable with no qualifications Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide 10 2 How to Use the Coefficient of Variation Tables to Obtain Confidence Limits 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 95 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 diff
59. ent of Sampling Error 25 Guidelines for Tabulation Analysis and Release eene 27 9 1 Rounding Guidelines een Dee e ag eb 27 9 2 Sample Weighting Guidelines for Tabulation sse 27 9 3 Categorical Estimates iie eget edenda alan deret ce La ec ede 28 9 3 1 Tabulation of Categorical Estimates nn 28 9 4 Guidelines for Statistical Analysis sse enne 28 9 5 Coefficient of Variation Release Guidelines pp 29 9 6 Release Cut off s for the National Tenant Satisfaction Survey pp 31 Special Surveys Division 3 National Tenant Satisfaction Survey 2004 User Guide 10 0 Approximate Sampling Variability Tables uunsunsnnnnesnsnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnannnnnannnnnn 33 10 1 How to Use the Coefficient of Variation Tables for Categorical Estimates 33 10 1 1 Examples of Using the Coefficient of Variation Tables for Categorical Estimate Sie AA E RA a ne Qu de 36 10 2 How to Use the Coefficient of Variation Tables to Obtain Confidence Limits 41 10 2 1 Example of Using the Coefficient of Variation Tables to Obtain Confidence Bcc EET 42 10 3 How to Use the Coefficient of Variation Tables to Do a T test ee 42 10 3 1 Example of Using the Coefficient of Variation Tables to Do a T test 43 10 4 Coefficient of Variation Tables nn 44 ATO Welghthg nmi ainena i aeea A eaaa i aeaa aAA Vaderia eskr
60. eral government departments or agencies participating in the National Tenant Satisfaction Survey and who are in buildings which have been identified by Public Works and Government Services Canada as under their responsibility and in scope for the survey Large buildings Buildings identified with 100 or more telephone lines Small buildings Buildings identified with less than 100 telephone lines Tenant Federal government employees who are occupants in the buildings Respondents Federal government employees who responded to the questionnaire Eligible cases The telephone lines which were verified as belonging to federal government employees in large buildings under the responsibility of PWGSC in participating departments and agencies i e in scope telephone numbers Response rate The number of federal government employees responding to NTSS as a percentage of the number of eligible cases Out of scope Telephone numbers which fell outside of the sample criteria Units were considered out of scope if the telephone numbers were those belonging to facsimile machines conference rooms data lines elevators or were identified as not belonging to a federal department or agency or were those of a department or agency who did not wish to participate in the survey Also some telephone numbers initially thought to be in scope were later verified to belong to buildings not under the responsibility of PWGSC or buildings not in scope
61. erence 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 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 appropriate table the coefficient of variation of the estimate X and then using the following formula to convert to a confidence interval CT CI io R 1 a where Qs is the determined coefficient of variation of X and t 1ifa 6896 confidence interval is desired t 1 6 if a 9096 confidence interval is desired t 2if 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 Special Surveys Division 41 42 National Tenant Satisfaction Survey 2004 User Guide 10 2 1 Example of Using the Coefficient of Variation Tables to Obtain Confidence Limits A 95 confidence interval for the
62. es not apply to Me nen Go to SS Q21 DK R SS Q20 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the office cleaning services 01 1 02 2 03 3 04 4 05 5 66 Does not apply to me SS_Q21 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of washroom cleaning services 01 1 02 2 03 3 04 4 05 5 66 Does not apply to Me nnne Go to SS Q23 DK RF Special Surveys Division 61 SS_Q22 SS_Q24 62 National Tenant Satisfaction Survey 2004 User Guide On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the washroom cleaning services oes not apply to me UUNAGON A On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of cleaning services for hallways elevators and common areas m cm A oes not apply to me pp Go to SS Q25 F On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the cleaning services for hallways elevators and common areas 1 2 3 4 5 Do
63. es not apply to me On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of reliability of elevators OPOD Does not apply to Me nen Go to S8 Q27 DK RF Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide SS_Q26 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the reliability of elevators 01 1 02 2 03 3 04 4 05 5 66 Does not apply to me DK SS Q27 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of accessibility of building for people with disabilities 01 1 02 2 03 3 04 4 05 5 66 Does not apply to Me nen Go to SS Q29 DK SS Q28 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with accessibility of building for people with disabilities 01 1 02 2 03 3 04 4 05 5 66 Does not apply to me SS Q29 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of building system noise levels 01 1 02 2 03 3 04 4 05 5 66 Does not apply to Me oocooccconoccccnoccconcncnoncnn
64. for the survey Special Surveys Division 11 National Tenant Satisfaction Survey 2004 User Guide 4 1 1 Participating Departments and Agencies Because of the changing nature of government department names with mergers and splits the list below may not be a current accurate and complete list of departments and agencies The list provided below is a snap shot of the list of department and agency names we had prior to finalizing the frame of telephone numbers for choosing the sample for the survey Agriculture and Agri Food Canada Association of Professional Executives of the Public Service of Canada Canadian Food Inspection Agency Canadian Heritage Citizenship and Immigration Canada Department of Finance Canada Department of Foreign Affairs Department of Justice Canada Environment Canada Fisheries and Oceans Canada Governor General Residence of Her Excellency Health Canada Indian and Northern Affairs Canada Industry Canada Infrastructure Canada International Trade Canada Library and Archives Canada Millennium Bureau of Canada National Defence Natural Resources Canada Office of the Auditor General of Canada Office of the Governor General of Canada Parks Canada Parliament of Canada Privy Council Office Public Safety and Emergency Preparedness Canada Public Works and Government Services Canada Royal Canadian Mounted Police Royal Society of Canada Solicitor General of Canada The Leadership Netw
65. ghts over or on too dark natural lighting from windows see eine job ae Na or laboratory table glare flickering 11 Elevators Elevator reliability speed service record i e frequency of repairs elevator unreliable elevator too slow elevator frequently breaks down out of service cleaning of elevators see 6 Cleaning Common Use Areas 78 Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide Description Include Exclude 12 ne Rise and hs of quality and availability of plumbing problems us m ng waterin tne drinking water in the hot and cold water for washing uilding building ni et maintenance of drinking water taste of drinking water fountains see 6 Cleaning Common Use Areas 13 Building Sound produced from noise level of noise from photocopiers printers System building mechanical building mechanical and other work related machinery Noise systems including systems furnaces fans see 7 Office Privacy E t air conditioning noise from repair construction 9 ete projects 14 Food Food services and related e food quality and variety cleaning of cafeteria see 6 Services Veneto ee N e cost of food Cleaning Common use areas location size of cafeteria Cafeteria hours cafeteria location or size 15 Parking un and a of availability of parking security see 16 Building Security P
66. i iabea S 51 12 0 Questionnailre a a a N 53 l2 76 AppendDCA nn 77 4 Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide 1 0 Introduction The National Tenant Satisfaction Survey NTSS was conducted by Statistics Canada from October 5 2004 to December 10 2004 with the cooperation and support of Public Works and Government Services Canada PWGSC This manual has been produced to facilitate the use of the survey results and microdata 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 Special Surveys Division 5 National Tenant Satisfaction Survey 2004 User Guide 2 0 Background The National Tenant Satisfaction Survey was undertaken to provide information on the satisfaction of federal public servants who work in buildings under the responsibility of Public Works and Government Services Canada PWGSC with regard to their physical working environment The survey collected information about employee workspace building services service availability changes in services and satisfaction with the property management team The survey was first conducted by Statistics Canada from December 11 2001 to March 15 2002 The resulting data and
67. iewer was either unable to contact the respondent or the respondent refused to participate in the survey Total non response was handled by adjusting the weights of individuals 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 not understand or misinterpreted a question refused to answer a question or could not recall the requested information If non respondents tend to differ from respondents in terms of the survey variables then a non response bias could be present To reduce the effect of any non response bias efforts were made to keep the response rate as high as possible Interviewers were instructed to make reasonable attempts to obtain NTSS interviews with tenants of participating departments and agencies For tenants who at first refused to participate in the NTSS a second call was made by the senior interviewer and a confirmation letter was sent by facsimile from the Regional Office to the tenant s office stressing the importance of the survey and the tenant s cooperation For cases in which the timing of the interviewer s call was inconvenient an appointment was arranged to call back at a more convenient time For cases where no one was in the office numerous call backs were made Special Surveys Division Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide 8 2 4 Measurement of Sampling Error
68. inde ni derent emen 65 SO id 65 SO na 65 952029 id 65 SO ii 66 952033 Li Nn 66 SSS Q34 00 nemen 66 SS OEE E 66 ON 67 95 037 ON 67 O ON 67 O 67 55 Q40 neenon peak 68 Ww WS B03 escono bee be etre 57 WS QOI sg ni mette 57 WS QOIS suonerie teen 57 WS 002 0 57 WS5 Q034 ne deed ede 57 WO 57 WS S Q05 ne 58 WS OO0SS ee 58 Special Surveys Division Appendix A National Tenant Satisfaction Survey 2004 User Guide The following was provided to interviewers to help them code appropriate responses to questions WS Q05 BSER_Q02 and BSER_Q04 Description Include Exclude 1 Air Quality Air quality including circulation or movement of air ventilation odours air quality air circulation air movement ventilation odours stuffiness amount of fresh air drafts stale or musty air temperature see 2 Temperature humidity see 2 Temperature odours from perfumes used by co workers allergens 2 Temperature Temperature or thermal comfort including heating air conditioning humidity temperature thermal comfort too hot or too cold heating air conditioning humidity adjustment of indoor temperature to outdoor temperature changes air quality circulation ventilation see 1 Air Quality capacity for personal temperature control 3 Office Size and layout of floor plan furniture repairs repl
69. ing 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 were taken to reduce 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 focus group testing of the questionnaire 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 The quality of some of the sampling variables on the frame were dependent on the timeliness and accuracy of the data from the telephone companies Due to inaccuracies on the frame it was possible that interviewers contacted employees Special Surveys Division 23 24 National Tenant Satisfaction Survey 2004 User Guide of government departments or agencies which were out of scope for the survey In these cases interviewers were instructed to apologize for the interruption and end the interview These telephone numbers were then coded as out of scope There were several other reasons why telephone numbers were considered to be out of scope When the list of telephone numbers were obtained from the telephone companies it was not
70. ion Survey 2004 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 9 2 Estimates in the main body of a statistical table are to be rounded to the nearest hundred units using 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 digits are between 50 and 99 they are changed to 00 and the preceding digit is incremented by 1
71. k ck ck ck ck A AH ck k ck ck kk 35 0 PRPRPRPRPENNNWSEA CORPBUDIDMONDANY gt C 61100610 N 1 Q0 2 IO Oo 4S NR WA FOB Y I COO Oro Oo 4 J 0o 6 40 0 NNUA O1 O1 O1 OY Ov O J CO OO tio IS C 4S O1 Oy 1 iO P UF C gt L3 NO NO On tO Bs O CO CO Q0 XO OY UI Oy iO 00 WO o ws KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK ck ck ck KKK ck ck KKK KKK KKK KKK KKK KKK KKK ck ck ck KKK KKK ck ck ck ck ck ck ck ck HH AH HH HH A RK Special Surveys Division please refer to the microdata documentation 50 0 NNN SB FWP 4S 4S U1U10103 0 200 toO No C0 4S O1 OY 1 O Q0 OO CO xe Q0 QO I O CQ OO CQ O O QJ CQ ND P C iO O H WO 49 e e PRPRPRPRPRPRPNW CORPRPNWUYEE NO OU oO Oy io NO N20 iO CO O0 C O J XO OI iO OO N N CO CO CO i ds ds BOD O OO jo 6 90 0 ber Oo O M FH p P PN NOS P U 0 U 0 ds Hs 01 01 01 Oy I CO C001 00 PC U1 2 CO CO CO OY COO JOGO C0 O QO QJ oO NUMERATOR OF PERCENTAGE 750 1 000 1 500 2 000 3 000 4 000 5 000 6 000 7 000 8 000 9 000 10 000 12 500
72. kc kk ck kk kk kk HH HH HH HH HH HH IR I I I III III III III III III ck ck ck ck ok oko ko ko ko ke 2 19 2k kc kc kk kk kk kk kk Sk Sk Sk Sk Sk Sk SK Sk Sk Sk Sk kk RI I ke ke kc ok ck kk ck ck ck ck ck RR RR I ck ck RR I ke ke ke e kk ck kk ck ck ck ck ck ck ck ck ck ckckck ckckckckckckckckckckckokokckokokck ko k ck a oe NOTE For correct usage of these tables please refer to the microdata documentation Special Surveys Division 45 90 0 PPRREN Ne 0 0 OU OQ io PS pP pP p MN MN OQ Q C CQ UY ds BH 01 01 Oy OO OW md ao N CO O1 oo NUMERATOR OF PERCENTAGE 750 1 000 1 500 2 000 3 000 4 000 5 000 6 000 7 000 8 000 9 000 10 000 12 500 15 000 20 000 NOTE For correct usage of these tables 46 45 6 7 8 8 0 9 0 oo 8 KKKKK KKK KKKKK KKK KKKKK KKK KKKKK KKK KKKKK KKK KKK KKK KK KKKKK KKK KKK KKK KK KKK KKK KK KKKKK KKK KKKKK KKK KKKKK KKK National Tenant Satisfaction Survey 2004 User Guide National Tenant Satisfaction Survey NTSS 2004 Approximate Sampling Variability Tables National Capital Region and Nunavut 0 2 5 5 7 7 8 6 0 8 3 9 8 6 8 4 2 2 7 4 oo 9 kk ck ck ckckckck ck ck ck ck ck KKK KKKKKKK KKK ck ck ck ck oko 10 0 O0 C0 OY 0 P C0 JJ EP OY OD ds 01 ds ds ND OB oo 5
73. mates 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 estimates 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 National Tenant Satisfaction Survey 2004 User Guide 9 6 Release Cut off s for the National Tenant Satisfaction 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 introduced in the previous section These cut offs are derived from the coefficient of variation CV tables discussed in Chapter 10 0 For example the table shows that the quality of a weighted estimate of 60 people possessing a given characteristic in the Atlantic Region 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
74. mine 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 employees in the Western Region who would like to see improvements to their physical work environment The denominator of the estimate x is the number of employees in the National Capital Region and Nunavut who would like to see improvements to their physical work environment 2 Refer to the coefficient of variation tables for the WESTERN REGION and the NATIONAL CAPITAL REGION AND NUNAVUT 3 The numerator of this ratio estimate is 5 318 The figure closest to it is 5 500 The coefficient of variation for this estimate is found by referring to the first non asterisk entry on that row in the WESTERN REGION CV table namely 1 1 4 The denominator of this ratio estimate is 49 337 The figure closest to it is 50 000 The coefficient of variation for this estimate is found by referring to the first non asterisk entry on that row in the NATIONAL CAPITAL REGION AND NUNAVUT CV table namely 0 6 5 So the approximate coefficient of variation of the ratio estimate is given by Rule 4 which is 2 2 Aj 0 0 where and are the coefficients of variation of x and X respectively That is a 0 011 0 006 0 000121 0 000036 0 013 6 The obtained ratio of Western Region versus National Capital Region and Nunavut employees who would like to see improv
75. nal Tenant Satisfaction Survey 2004 User Guide 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 If using the automated method follow the same instructions as in Rule 1 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 where x is estimate 1 X is estimate 2 and and a are the coefficients of variation of X and X respectively The coefficient of variation of d is given by d This formula is accurate for the difference between separate and uncorrelated characteristics but is only approximate otherwise If using the automated method the CVs can be obtained as in Rule 1 and then insert the values into the formula above 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 employees in the National Capital Region and Nunavut and the numerator is the number of employees in the National Capital Region and Nunavut who would like
76. nonannano cnn nc cnn nn nana n cnn Go to SS_Q33 DK RF Special Surveys Division 63 SS_Q30 SS_Q34 64 National Tenant Satisfaction Survey 2004 User Guide On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the building system noise levels oes not apply to me UUNAGON A On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of the food services oes not apply to me pp Go to SS Q35 m cm A On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the food services 1 2 3 4 5 Does not apply to me On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of privacy OPOD Does not apply to me Ne Go to SS Q37 DK RF Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide SS_Q36 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the privacy 01 1 02 2 03 3 04 4 05 5 66 Does not apply to me DK SS Q37 On a
77. not report Yes No tr a Abert eile ented Go to BSER_Q12 Boucle P tt tna toi Go to BSER_Q12 Why did you not report this issue to anyone INTERVIEWER Mark all that apply Thought someone else would report Don t know who to report to Thought nothing would be done anyway Wasn t important to me Embarrassed Rude unpleasant staff Worried about the repercussions Other Specify auti ai Gn RR E t ade Go to BSER_Q11S DK RF Goto BSER Q12 Why did you not report this issue to anyone _ 80 spaces Do you deliver Real Property services to employees of your department INTERVIEWER Definition manage day to day Facilities Management operations ie parking signage move management telecom management etc Yes NO 2 2 A bereit recidere ee da PO ee cr d de Go to CAI SO DIRE iei SIEHE TORE EN ive dn dn Go to CAI SO Overall how satisfied are you with the ability of your building s property manager managers team to support your business and operational needs INTERVIEWER Read categories to respondent Very satisfied Somewhat satisfied Somewhat dissatisfied Very dissatisfied DK RF Special Surveys Division 73 BSER_Q14 BSER_Q15 01 02 03 04 05 66 BSER_Q16 BSER_Q17 74 National Tenant Satisfaction Survey 2004 User Guide On a scale of 1 to 5 where 1 is lowest and 5 is highest please rate your satisfaction with the following aspects from the property management team
78. o 1 year ago are there any services which have deteriorated Yes NO ee ME RR HEN Go to BSER Q05 DIC BE sen reticere exeo eee used ade Go to BSER Q05 Special Surveys Division BSER_Q04 Default Note BSERQ04S BSER_Q05 ROND National Tenant Satisfaction Survey 2004 User Guide Which ones INTERVIEWER Mark all that apply Air Quality Temperature Office Size Layout Cleaning Office Areas Cleaning Washrooms Cleaning Common Use Areas Office Privacy Noise Lighting Natural Lighting Overhead Lighting Task Elevators Drinking Water Building System Noise Food Services Parking Building Security Shower Facilities Interior Finishes Furniture Accessibility of building for people with disabilities Other Specify an ana al Go to BSER_Q04S DK RF Go to BSER_Q05 Attached is the contents to be displayed on the help screen for this question Are there any other services which have deteriorated _ 80 spaces Overall how satisfied are you with the services in your building INTERVIEWER Read categories to respondent Very satisfied Somewhat satisfied Somewhat dissatisfied Very dissatisfied DK RF Special Surveys Division 71 BSER_Q06 OPO OD Default BSERQ06S BSER_Q07 4 2 BSER_Q08 _ BSER_Q09 Default BSERQ09S 72 National Tenant Satisfaction Survey 2004 User Guide To whom would you report problems or concerns in your b
79. ork Transport Canada Treasury Board of Canada Secretariat Veterans Affairs Canada Some departments and agencies elected not to participate in this survey They include Canada Border Services Agency Canada Revenue Agency Canadian Security Intelligence Service Human Resources Development Canada Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide 4 2 Survey Definitions Physical work environment Services in buildings including cleaning lighting cafeteria food office space etc Parking availability Refers to publicly managed parking lots Task lighting Special lights over or on the immediate work area Natural lightin Light coming through windows or skylights Air quality Quality of the air in the buildings including air movement and odours Building security services Security guards perimeter doors and management of after hours building access Barrier free accessibility to the building Easy entry into the building for people with disabilities such as wheelchair ramps Building system noise levels Noise levels of furnaces fans and air conditioning Real property or facilities management The people responsible for the management service of property assets and their equipment to employees within their department Property manager The person responsible for the day to day operations of buildings and specialized facilities This includes planning budgeting energy management
80. province What is the building s address INTERVIEWER Enter address NUM Enter the civic number 5 bytes STREET Enter the street name 50 bytes APT Enter the suite number 5 bytes CITY Enter the city name 30 bytes PROV Enter the province 2 bytes POSTAL CODE Enter the postal code 6 bytes do not allow blanks only DK or RF allowed for non response Accept only 5 characters for civic number 50 characters for street name 30 characters for city name and 2 characters for province Is the name of your department department name Yes Noo cat tel cta cec Mee eat obs de cna le te Go to SI Q07A DK RF Go to WS Q01 department name comes from Database Display only first 80 alpha numeric characters If blank then go to SI Q07S What is the name of your department 4 spaces Programmer Note Use Excel spread sheet to create trigram A four digit code should be returned See note on trigram spec for further instructions What is the name of your department _ 80 spaces Workspace WS INTERVIEWER Enter gender Male Female DK RF Special Surveys Division Default WS Q01S National Tenant Satisfaction Survey 2004 User Guide Which of the following best describes your workspace INTERVIEWER Read categories to respondent A single office in open concept cubicle A shared office in open concept shared cubicle A closed office not shared A closed office shared A warehouse A laboratory
81. 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 region which were used to produce the Approximate Sampling Variability Tables for the National Tenant Satisfaction Survey NTSS Atlante 1 344 7 187 Quebec excluding National Capital Region 1 091 6 399 National Capital Region and Nunavut 5 289 80 667 Ontario excluding National Capital Region 3 632 Western includes Northwest Territories 1 227 9 392 Pacific includes Yukon 3 102 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 10 1 How to Use
82. respondents out of scope units and duplicates Step 3 An adjustment to account for the fact that one telephone number could be linked to several employees Question SI Q04 asked the respondent how many people were using the selected telephone number The second adjustment uses the response to SI Q04 to adjust the final weight to account for this one telephone number to many employees relationship Step 4 The final weight is calculated as FINAL WEIGHT WEIGHT A1 SI _ Q04 This weight is required in order to produce meaningful estimates from the survey data Special Surveys Division 51 12 0 National Tenant Satisfaction Survey 2004 User Guide Questionnaire The National Tenant Satisfaction Survey questionnaire was used from October to December 2004 to collect the information for the survey DK represents Don t know responses RF represents Refusal responses Section SI_101 MON R01 SI Q04 Note SI Q05 Default Note SI Q05S Survey Introduction SI We are doing a survey of Federal Government employees in buildings under the responsibility of Public Works and Government Services Canada PWGSC concerning the quality of services This information will help PWGSC to better understand your needs and use the information to improve the services in your building Your opinion is very important Your answers will be kept confidential under the Statistics Act and
83. scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of drinking water 01 1 02 2 03 3 04 4 05 5 66 Does not apply to Me nen Go to SS Q39 DK RF SS Q38 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the drinking water 01 1 02 2 03 3 04 4 05 5 66 Does not apply to me SS Q39 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of shower facilities 01 1 02 2 03 3 04 4 05 5 66 Does not apply to Me Go to SA 101 DK RF Special Surveys Division 65 SS_Q40 Section SA_101 SA_Q01 66 National Tenant Satisfaction Survey 2004 User Guide On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the shower facilities 4 2 3 4 5 Does not apply to me Service Availability SA Using the same scales we would like to know the importance of having specific services available in your building or in the surrounding areas and your level of satisfaction regarding their availability On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how wo
84. tion to find very approximate CV values for the averages for the importance and satisfaction questions To find the CV for the average the user enters the average in the right hand side of the window selects the appropriate geographical region and clicks on the calculate CV button Rule 1 Estimates of Numbers of Persons Possessing a Characteristic Aggregates An estimate of the number of people possessing a characteristic can be obtained from the tables of results by multiplying the percentage given in the cell of the HTML tables by the appropriate population value given in the second last row or column of the table The coefficient of variation depends only on the size of the estimate itself On the Approximate 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 If using the automated method for calculating the CVs the user enters the percentage of interest from the HTML table and the population value given in the appropriate column or row of the HTML table These are entered in the left hand side of the window Next the user selects the geographic region to which the estimate applies and then clicks on the calculate CV button The approximate CV for the percentage as well as the estimate of the
85. tness facilities 01 1 02 2 03 3 04 4 05 5 66 Does not apply to me DK RF Special Surveys Division 67 SA_Q07 SA_Q09 68 National Tenant Satisfaction Survey 2004 User Guide On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of access to shopping areas UUNAGON A oes not apply to me pp Go to SA Q09 RF On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the access to shopping areas oes not apply to me m cm A On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of access to bank machines 4 2 3 4 5 D oes NOt Apply tO ME cepi eier Go to SA Q11 RF On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the access to bank machines OPOD Does not apply to me DK RF Special Surveys Division SA Q11 01 02 03 04 05 66 Section BSER STR Note BSER Q01 1 2 National Tenant Satisfaction Survey 2004 User Guide On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how
86. to see improvements to their physical work environment In the case where the numerator is not a subset of the denominator as for example the ratio of the number of employees in the National Capital Region and Nunavut who would like to see improvements to their physical work environment as compared to the number of employees in the Pacific Region who would like to see improvements to their physical work environment the standard error 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 X X is p 2 2 o Rya 0 where a and are the coefficients of variation of X and X respectively The coefficient of variation of R is given by o R The formula will tend to overstate the error if o and E are positively correlated and understate the error if x and X are negatively correlated If using the automated method the CVs can be obtained as in Rule 1 and then insert the values into the formula above Special Surveys Division 35 National Tenant Satisfaction Survey 2004 User Guide 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
87. ty of building for people with disabilities Other Specify at an ae ee dece dei ete duca Go to WS Q05S DK RF Goto SS 101 Attached is the contents to be displayed on the help screen for this question Which improvements would you like to see made to your physical work environment and related services in your building 80 spaces Satisfactory Service SS In the following section you will be asked to rate specific services in terms of their importance to you personally and your level of satisfaction regarding these services If some services do not apply to you please answer Service does not apply to me On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of natural lighting for you 1 2 3 4 5 Does not apply to Me Go to SS Q03 Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide SS_Q02 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the natural lighting 01 1 02 2 03 3 04 4 05 5 66 Does not apply to me DK SS_Q03 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of task lighting 01 1 02 2 03 3 04 4 05 5 66 Does not apply to Me nen Go to SS Q05 DK
88. uilding INTERVIEWER Read categories to respondent Administration area pe Go to BSER_Q10 Departmental contact or supervisor sssss Go to BSER Q10 1 800 number PWGSC National Service Call Centre PWGSC Property Manager Other Specify sesssssssssssssseeeneen entren Go to BSER Q06S DKS RE Se atch mu A nee A nd Eris Liu Go to BSER Q10 Go to BSER Q07 To whom would you report problems or concerns in your building 80 spaces Have you ever reported a problem or concern to one of these people Yes Go to BSER_Q10 DIRE An ce ad dva ei Go to BSER_Q10 How often were the problems or concerns resolved or answered to your satisfaction INTERVIEWER Read categories to respondent Always Ri Go to BSER_Q10 Sometimes Never DK RES a LC Go to BSER_Q10 Why were you not completely satisfied with the response INTERVIEWER Mark all that apply Slow response to concern complaints Rude unpleasant staff Poor bad service Problem still exists Nobody came to solve the problem Poor communication Other Specify iiec oerte nier or idea Go to BSER Q09S DK RF Go to BSER_Q10 Why were you not completely satisfied with the response 80 spaces Special Surveys Division BSER_Q10 1 2 BSER_Q11 Default BSERQ11S BSER_Q12 _ BSER_Q13 AON National Tenant Satisfaction Survey 2004 User Guide Did you ever have a problem that you did
89. uirements for the NTSS 2004 were to produce reliable estimates at the management type by region level 34 in all and reliable estimates for over 30 priority buildings specified by the external client each building can appear in only one region and it can only have one type of management In both cases the minimum estimable proportion was set at 0 15 Special Surveys Division 15 National Tenant Satisfaction Survey 2004 User Guide min p The requirements for the NTSS 2004 are an important departure from those of the 2002 2003 survey The following requirements were used to determine the original sample allocation the total sample size was set at approximately 20 000 telephone numbers the minimum estimable proportion at the management type region and pre specified building levels were set at 0 15 min p We calculated the number of responses needed at the management type and region level in order to be able to estimate a proportion of 0 15 with a coefficient of variation CV of 16 596 This was achieved using the Kish allocation This type of allocation offers a compromise between proportional and equal allocation The sample selection took place at the stratum level Telephone numbers were randomly selected using simple random sampling within a stratum The distribution of the sample by region is given in the table below Region Sample Size Atlantic 2 417 Quebec excluding National Capital Region 2 300 National C
90. uld you rate the importance of access to public transportation oes not apply to me Nt Go to SA Q03 UUJNAGDN A On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the access to public transportation 4 2 3 4 5 Does not apply to me Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide SA_Q03 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of access to daycare 01 1 02 2 03 3 04 4 05 5 66 Does not apply to Me entrent Go to SA Q05 DK RF SA QO04 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the access to daycare 01 1 02 2 03 3 04 4 05 5 66 Does not apply to me DK SA Q05 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of access to fitness facilities 01 1 02 2 03 3 04 4 05 5 66 Does not apply tO MC i i a A nae cnn an cnn cnn nn Go to SA Q07 RE SA_Q06 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the access to fi
91. use the estimate is a percentage which is based on a subset of the total population i e employees who had worked in the same building for at least one year it is necessary to use both the percentage 33 0 and the numerator portion of the percentage 1 664 in determining the coefficient of variation 3 The numerator 1 664 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 1 700 Similarly the percentage estimate does not appear as any ofthe column headings so it is necessary to use the percentage closest to it 35 0 National Tenant Satisfaction Survey NTSS 2002 2003 Approximate Sampling Variability Tables for Quebec excluding National Capital Region NUMERATOR OF PERCENTAGE ESTIMATED PERCENTAGE 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 wow 61 5 61 2 602 586 570 553 535 51 7 498 479 43 7 33 8 20 ee 485 433 426 4 5 40 3 39 1 378 366 352 33 8 30 9 239 30 wer 355 353 0348 338 329 319 309 299 288 276 252 19 5 40 se 30 7 306 30 1 293 285 276 268 259 249 239 218 16 9 1400 Hr Sabido KEKEREKE Orton dekdekekdekek kkkkkkkk 4 5 4 4 4 2 4 0 3 7 2 9 500 Fr Re ie SERIE dekdekkdekek kkkkkkkk KK AAA AR 4 4 42 4 1 3 9 3 6 2 8 1600 dekdekkdekek kkkkkkkki kkkkkkkk kkk kkk k dekdekkdekek kkkkkkkk KARA ARA AAA 4 1 3 9 3 8 3 5 2 7 1700 kkkkkkkk 212 2127222 52 Base 2323212
92. vey using the telephone numbers provided by the contractor The telephone numbers in buildings and departments or agencies in scope for the survey were identified by Statistics Canada personnel The files included a field indicating the department or agency to which the telephone numbers belonged Any buildings which contained only telephone numbers belonging to the departments or agencies which chose not to participate in the survey were removed from the frame In cases where several buildings were part of a complex e g East Tower West Tower etc it was not always possible to determine to which building a telephone number belonged The only information available was that it belonged to the complex as a whole In these cases some or all of the buildings within the complex had to be combined on the frame and treated as one building The final frame contained telephone numbers for 272 buildings There were a total of 140 999 telephone numbers on the frame All survey results relate to the buildings on the final frame 5 2 1 Stratification The NTSS is based on a stratified design with simple random sampling within strata Telephone numbers were used as the sampling unit and the strata were defined as the buildings 5 2 2 Sample Allocation and Selection When calculating the sample size some assumptions were necessary The rate of out of scope telephone numbers on the frame was expected to be 3596 and the response rate 8096 The survey req
93. will be used only for statistical purposes While participation is voluntary your assistance is essential if the results of the survey are to be accurate Registration STC SSD 040 75221 Before we begin I would like to let you know that this call may be monitored for survey quality control INTERVIEWER Press Enter to continue How many people are using telephone number extention number 8 spaces Min 1 Max 995 telephone number and extention number come from Database If extention number is blank then show telephone number only Is the name of your building building name Yes GO Go to SI Q05S p ebllum Go to SI Q06 Go to SI Q06 building name comes from Database Display only first 80 alpha numeric characters If blank then go to SI Q05S What is the name of your building 80 spaces Special Surveys Division 53 SI Q06 Default Note SI N06 Note SI Q07 _ Default Note SI_Q07A Note SI Q07S Section SEX Q01 1 2 54 National Tenant Satisfaction Survey 2004 User Guide Is the address of your building building address Yes NO eui ar LANI MAL LE Go to SI N06 DK RE Hrn PE Go to SI Q07 Go to SI Q07 building address comes from database Display only 5 characters for civic number 50 characters for street name 30 characters for city name and 2 characters for
94. would you rate the importance of access to bike racks oes not apply to me pp Go to BSER STR COOOROonm A On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the access to bike racks oes not apply to me m cm A Building Services BS CHECK If WS_Q02 1 or WS_Q02 DK or WS_Q02 RF then go to BSER_Q05 Else go to BSER Q01 Compared to 1 year ago are there any services which have improved Yes NO Go to BSER_Q03 BIETER Go to BSER Q03 Special Surveys Division 69 BSER Q02 Default Note BSERQ02S BSER_Q03 70 National Tenant Satisfaction Survey 2004 User Guide Which ones INTERVIEWER Mark all that apply Air Quality Temperature Office Size Layout Cleaning Office Areas Cleaning Washrooms Cleaning Common Use Areas Office Privacy Noise Lighting Natural Lighting Overhead Lighting Task Elevators Drinking Water Building System Noise Food Services Parking Building Security Shower Facilities Interior Finishes Furniture Accessibility of building for people with disabilities Other Specify da dtt ee a ge cede e at Go to BSER_Q02S DK RF Go to BSER Q03 Attached is the contents to be displayed on the help screen for this question Are there any other services which have improved _ 80 spaces Compared t
95. y the number of respondents who reported SEX men 3 for each of these respondents calculate a RESCALED weight equal to the original person weight divided by the AVERAGE weight 4 perform the analysis for these respondents using the RESCALED weight However because the stratification 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 NTSS 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 0 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 0 to be more fully aware of the quality characteristics of these data First the number of respondents who contribute to the calculation
96. you rate your level of satisfaction with the outside lighting oes not apply to me vUurom A On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of building security services after hours access amp security guards UUJNAGON A oes not apply to me pp Go to SS_Q17 R On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the building security services after hours access 8 security guards 4 2 3 4 5 Does not apply to me On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of snow removal OPOD Does not apply to Me pp Go to SS_Q19 DK RF Special Surveys Division National Tenant Satisfaction Survey 2004 User Guide SS_Q18 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate your level of satisfaction with the snow removal 01 1 02 2 03 3 04 4 05 5 66 Does not apply to me DK SS Q19 On a scale of 1 to 5 where 1 is lowest importance or satisfaction and 5 is highest importance or satisfaction how would you rate the importance of office cleaning services 01 1 02 2 03 3 04 4 05 5 66 Do

Microdata User Guide NATIONAL TENANT SATISFACTION SURVEY

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