This document discusses sampling techniques for online surveys. It distinguishes between populations and samples, and identifies probability sampling techniques like simple random sampling, systematic sampling, stratified sampling, and cluster sampling. It also identifies nonprobability sampling techniques like convenience sampling and snowball sampling. The document emphasizes evaluating sample size and sources of error in survey samples, like coverage error, nonresponse error, and sampling error. It provides guidelines for determining an appropriate sample size based on the desired confidence level and margin of error.

1. Conducting
ONLINE SURVEYS
Valerie M. Sue, Ph.D.

2. 3. Sampling

3. Learning Objectives
1 Distinguish populations & samples
2 Identify probability sampling techniques
3 Identify nonprobability sampling techniques
4 Evaluate sample size issues
5 Explain sources of error in survey samples

4. Populations
& Samples

5. Population Set of all units
Sample
Subset of a
population

6. 6

7. 7

8. List of
Sampling
frame population
members

9. Sampling
Techniques

10. Saturation Sampling:
survey everyone (census)

11. Probability
Sampling
Participants are
randomly selected

12. Closed Open
12
populations populations
 Simple random  Intercept
 Systematic  Prerecruited
panel
 Stratified
 Cluster

13. Simple random:
every member has an equal
chance of being selected

14. Systematic:
select first person at random,
then select every nth person

15. Stratified:
select random samples within
population subgroups
Group A Group B
Group C

16. Cluster:
randomly select preexisting
groups—
everyone in selected group
is surveyed

17. Intercept:
interrupt browsing, invite
every nth visitor to respond

18. Prerecrutited panel:
randomly select members
who have previously agreed
to participate

19. Nonprobability
Sampling
Participants are NOT
randomly selected

20. Convenience:
20
surveyor selects handy group

21. Volunteer opt-in:
21
Participants self-select
into the sample

22. Snowball:
participants refer associates

23. How large should
the sample be

24. When using
simple random
samples

25. 90% 95% 99%
Margin of
Confidence Confidence Confidence
Error
Level Level Level
± 5% 272 384 666
± 4% 425 600 1,040
± 3% 756 1,067 1,849
± 2% 1,702 2,401 4,160
± 1% 6,806 9,604 16,641

26. When using
nonprobability
samples

27. Rules of thumb
30 to 500
About 10% of population
Enough for subsample analysis
10 times more than the number of variables
As large as budget allows

28. Sources of

29. Coverage error:
sampling frame doesn’t
represent population

30. Nonresponse error:
some selected members
choose not to participate

31. Sampling error:
difference (due to chance)
between sample statistic and
population parameter

32. Summary

33. Selecting samples from
33
populations
Coverage error
Probability
Nonresponse error
Evaluate Simple random
Sampling error
sources of Systematic
error
Stratified
Cluster
Intercept
Determine Prerecruited panel
sample Nonprobability
size
Convenience
Choose sampling Volunteer
technique: Snowball
probability or
nonprobability