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Census and Statistics Department Introduction to Sample Surveys.

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Presentation on theme: "Census and Statistics Department Introduction to Sample Surveys."— Presentation transcript:

1 Census and Statistics Department Introduction to Sample Surveys

2 Census and Statistics Department Sample Surveys Sample survey has widespread applications, ranging from surveys conducted for business purposes to collection of data for use in public affairs and social studies. In order to ensure the reliability of survey results, it is essential that great care in addition to adequate professional knowledge be applied in the planning and conduct of surveys and in the analysis of data.

3 Census and Statistics Department Major Steps in Conducting a Sample Survey Overall planning Design and selection of sample Design of questionnaire Collection of raw data Compilation and analysis of statistics and dissemination of survey results

4 Census and Statistics Department Overall Planning Clearly defined survey objectives Clearly defined target population Clearly defined statistical standards (definition of terms, counting rules, classification, statistical methodologies) Respondents should be able to provide the information required. Adequate resources such as manpower and time must be available.

5 Census and Statistics Department Design and Selection of Sample Sampling deals with the selection of a number of elements, i.e. a sample. A sample can be drawn using different methods. A probability sample, with each element having a known, non-zero chance of being included, should be used as far as practicable so that scientific inference can be drawn from the survey results.

6 Census and Statistics Department Design and Selection of Sample Non-probability sampling methods, such as haphazard sampling, should be avoided. Such methods are not scientific and bias usually exists in survey results. A complete and up-to-date sampling frame should be acquired.

7 Census and Statistics Department Design and Selection of Sample In case of unequal probability of selection, it is necessary to ensure that proper weighting methods are applied to survey results. Using established statistical methodology to compute the required sample size. Once the sampling units are selected, alterations are not allowed.

8 Census and Statistics Department Common Probability Sampling Methods Simple random sampling Systematic sampling Stratified sampling Clustering sampling Multi-stage sampling

9 Census and Statistics Department Non-probability Sampling Methods Selection of elements is based on subjective judgment and experience, but not a random manner Common non-probability sampling methods Street interview/mall intercept Quota sampling Respondent-initiated telephone polling Internet survey

10 Census and Statistics Department Non-Probability Sampling Methods Why unreliable? Scientific inference cannot be drawn from the sample data (results are confined to describing the group of respondents, but cannot be extracted to the entire population) Level of precision of the estimates cannot be scientifically assessed Biases will most likely exist in the survey results

11 Census and Statistics Department Non-Probability Sampling Methods Why unreliable (contd)? No way to know how exactly the group of respondents is formed In street interviews, the interviewers tend to select those friendly faces for interview. In self-selecting polls, only those who have strong views on the survey may volunteer to participate. The results may be inaccurate and misleading, hence not of much use.

12 Census and Statistics Department General Principles in Designing Questionnaires Questions should be relevant to the survey objectives Questions should be arranged in a proper order Use screening question to enhance the flow of the questions. Use an appropriate language Clear instructions

13 Census and Statistics Department General Principles in Designing Questionnaires Questions wordings should be appropriate, specific and precise Avoid leading questions or questions being loaded in favour of a particular response Avoid difficult vocabulary Avoid composite and double negative questions Beware of memory error

14 Census and Statistics Department General Principles in Designing Questionnaires Dont know/No opinion should be included as appropriate Long questionnaires are undesirable. Questionnaires should be tested on some prospective respondents before finalized.

15 Census and Statistics Department Collection of Raw Data Methods of data collection for surveys include: Self-administered questionnaires by mail Personal interviews Telephone interviews Computer Assisted Telephone Interviewing (CATI) Very often, mixed modes of data collection can be used.

16 Census and Statistics Department Collection of Raw Data An appropriate mode should be selected by carefully considering respondents' willingness to co-operate, the degree of complexity of the subject of enquiry and other relevant factors (e.g. practicability of using personal or telephone interviews).

17 Comparison of Different Data Collection Methods CharacteristicsPersonal interview Telephone interview Mail questionnaire CostHighMediumLow ManpowerHighMediumLow Time consumingHighMediumLow Non-response/ non-contact rate Relatively lower Medium to high High Suitability for scattered population CostlyLess costly edium Interviewer biasYes No Response qualityHighMediumLow Length of questionnaireMay be longer Preferably short Design of questionnaireMay be more complicated Simple Asking embarrassing questions Not suitableEasier

18 Census and Statistics Department Collection of Raw Data Interviewers should be trained before they start working and closely supervised during fieldwork to ensure their quality of work. Identity and information supplied by individual respondents should be kept confidential. The survey results are to be presented in the form of aggregate statistics.

19 Census and Statistics Department Collection of Raw Data Every effort should be made to achieve a high response rate (or reducing the number of non-responses). Methods to reduce non-responses: Keep the questionnaire brief and concise Consider rewards to respondents Better publicity measures (e.g. advertisement, advance letters) Assurance of confidentiality of individual data

20 Census and Statistics Department Collection of Raw Data Methods to reduce non-responses (Contd) : More experienced interviewers, especially when handling refusals Visit households in evening time Visit at different time of different days Increase the number of re-visits/call backs Use self-administered questionnaires in case of non-contact

21 Census and Statistics Department Compilation and Analysis of Statistics Data should be carefully and thoroughly checked before compilation. Appropriate statistical methodology should be adopted in compiling and analysing data.

22 Census and Statistics Department Reporting and Assessing the Reliability of Surveys To enable readers to make judgment on whether the findings are credible, a good survey report should include: Sponsorship of the survey Population covered Sampling method Mode of data collection Time period of data collection Wording of questions

23 Census and Statistics Department Reporting and Assessing the Reliability of Surveys A good survey report should include (contd): Sample size and response rate Point estimates and confidence intervals (if possible) Likely sources of non-sampling errors Information supplied by individual respondents should not be disclosed.

24 Census and Statistics Department Reporting and Assessing the Reliability of Surveys One may access the reliability of a survey by asking the following questions : Has probability sampling methods been used ? Is the sample size reasonably large ? Is the questionnaire design proper ? Any leading questions or wordings ?

25 Census and Statistics Department Reporting and Assessing the Reliability of Surveys One may access the reliability of a survey by asking the following questions (contd): What is the interviewing method ? Any improper influence by interviewers or third parties during the interview ? Is the response rate too low ? Are the sampling errors of acceptable magnitude ? How about non-sampling errors and biases ?


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