1. INFO 271B LECTURE 9 COYE CHESHIRE Sampling

2. Agenda Info 271B 2 Non-probability Sampling Probability Sampling Probability Distributions

3. Why Sample? Info 271B 3 Drawing populations versus ‘samples’  E.g., survey of iSchool masters students Reducing Error

4. Non-Probability Sampling Info 271B 4 Quotas  Pick key groups of interest and find individuals to fill specific goals (i.e., 100 people in each key group).  Quotas are fulfilled without using random sampling Purposive Sampling  Find key groups and only study them

5. More Non-Probability Sampling Info 271B 5 Convenience Sampling  Taking anyone you can get to participate Snowball Sampling  Find starting point and use these individuals to get next participant…and so on

6. Probability and Probability Sampling 6 Are the things that we observe different from what would be expected by chance?

7. Real-World Example: Attitudes About the President (1-5 Likert Scale) 7

8. Do men and women differ in their assessment of the US president? 8

9. Probability Sampling Info 271B 9 Sampling Frames  A list of units of analysis from which you take a sample and to which you generalize  Directories, local census, etc. But, often cannot get an adequate sampling frame  Field research

10. How Large of a Sample? Info 271B 10 Sample Accuracy versus Sample Precision Key Issues for Determining Sample Size: 1) Heterogeneity of Population 2) Number of Subgroups 3) Size of Subgroup 4) Precision of sample statistics

11. Randomized Samples Info 271B 11 Simple Random Sample  Requires numbering all potential participants in a given sampling frame (N)  Pull random numbers from any source, use these as the sample (n)  Select n units out of N such that each N C n has and equal chance of being selected. Issues…  True randomization?  Replacement “in the field”

12. Systematic Random Samples Info 271B 12 Random start and sampling interval  (Sample x Interval = Population) Issues  Periodicity  Poor sampling frames (www.socialresearchmethods.net)www.socialresearchmethods.net

13. Info 271B 13

14. Stratified Random Sampling Info 271B 14 Key Issue: Representation of salient sub-populations  Maximize between-group variance while minimizing within-group variance Proportionate Samples  Do you know the key independent variables?  If not, may be better off avoiding stratification Disproportionate Samples  Weighting

15. Complex Sampling Designs Info 271B 15 Cluster Sampling  No available frames  Based on areas, institutions, or ‘clusters’