Class 14

1. Class 14 Statistical Inference Survey Research

2. Class Outline • Statistical Inference • Sampling Error • Sampling Distribution • Point Estimate and Confidence Interval • Survey Research • Asking Questions • Advantages and Disadvantages of Various Survey Methods • Secondary Data Analysis

3. Sampling Error • We are interested in certain characteristics of a population. These characteristics are called population parameters. • We do not observe the whole population. Instead, we draw a sample and calculate sample statistics. • We use sample statistics to estimate population parameters. • Differences between population parameters and sample statistics that are due only to chance factors are called sampling error. • The magnitude of sampling error can be estimated statistically.

4. Point Estimate and Interval Estimate • When a population parameter is estimated by a single number, that number is called a point estimate. (Point estimate is unlikely to be the true population parameter.) • An interval estimate of the population parameter m consists of two bounds within whichmis estimated to lie. That is, L£m£U, where L is the lower bound, and U is the upper bound.

5. Confidence Levels and Confidence Interval • Statistical inference: Suppose that we draw a sample of 100 families and measure their income. The mean income comes to $40000, and the standard deviation is $5000. Then the true population parameter for mean family income lies between (39020, 40980) with a probability of 95%. • A confidence interval is the interval within which you believe that the true parameter lies with a fixed probability. That probability is called the confidence level. • The 95% confidence interval is calculated as Confidence interval Confidence level

6. Sampling Distributions • Sampling distribution is a hypothetical distribution of a statistic (such as the mean) across all the random samples that could be drawn from a population. • Intuition: larger samples result in a sampling distribution more tightly clustered around the population mean. That is, the larger the sample size, the less the sampling error. • A larger sample size means a smaller confidence interval for the population parameter. • Stata demo: sample mean distribution (smddemo)

7. Determining Sample Size • Less sampling error is desired  larger sample is needed • Homogeneous population  smaller sample may be adequate.

8. Errors in Survey Research • Two common sources of survey errors • Errors of observation (poor measurement) • Errors of non-observation (omission of cases that should have been included in the sample)

9. Basic Modes of Survey • Self-administered mail survey • Face-to-face interview survey • Telephone interview survey • Web survey • Multi-mode survey

10. Guidelines for Asking Questions • Use the right question forms • Closed- vs. open-ended questions. • Contingency questions with clear instructions on skip pattern. • Matrix questions. • Use mutually exclusive and exhaustive categories.

11. Guidelines for Asking Questions • Avoid ambiguity. • native American; residential location • Avoid double-barreled questions. • Do you think the President should be impeached and compelled to leave the presidency? • Avoid negative items. • Do you agree that there should not be a tax increase?(Does “no” mean tax increase or no tax increase?) • Avoid double-negatives. • Does it seem possible to impossible to you that the Nazi extermination of the Jews never happened? • Avoid biased items and terms. • Assistance to the poor vs. welfare • Halting rising crime rate vs. law enforcement

12. Guidelines for Questionnaire Construction • Respondents must be competent to answer. • Respondents must be willing to answer. • Short items are best. • Decide whether to add an explicit neutral response category. • Eliminating the “neutral” category reduces fence-sitting. • Adding the “neutral” category reduces floating.

13. Questionnaire Design • Include instructions for the questionnaire. • Be aware of issues with ordering items. • Use existing question sets if available (e.g. CES-D scale of depression) • Pretest the questionnaire.

14. Improving the Response Rate • Give an incentive (gift, cash). • Send a notification letter. • Follow up on non-response. • Mail survey: send a reminder. • Face-to-face or telephone survey: Vary the days and times to visit/call. • Probe

15. Self-Administered MailSurvey • Advantages • Low cost • Can offer anonymity • Disadvantages • Requires literacy • Low response rates (non-response biases) • Can only ask simple questions • Interviewer cannot observe

16. Face-to-face Interview Survey • Advantages • Fewer incomplete questionnaires • Higher response rate • Interviewer can take observation notes • Appropriate for complex questionnaires • Allows for relatively long questionnaires • Disadvantages • Higher cost • Slow field work • Interviewer effects

17. Telephone Interview Survey • CATI (computer-assisted telephone interview) • Advantages • Lower cost than interview surveys • Quick implementation • Easier to supervise field work • Disadvantages • Questions must be short and simple • Answering machines

18. Web Survey • Advantages • Low cost • Quick implementation • Data entry errors are eliminated • Quick results • Can program contingency questions • Disadvantage • Selective sample • Not good at ensuring completion

19. Comparison of Various Survey Modes

20. Secondary Data Analysis • Secondary data analysis has become the primary means of conducting empirical research. • Reasons: • Concern with generalizability. • Increased cost of conducting independent surveys. • Wide availability of existing data, such as GSS.