conductingonlinesurveys_sue_ch3
DESCRIPTION
Presentation to accompany chapter 3 in "Conducting Online Surveys," (Sage Pub., 2012).TRANSCRIPT
Conducting ONL I NE SURVEYS
Valerie M. Sue, Ph.D.
Sampling 3.
Learning Objectives Distinguish populations & samples 1 Identify probability sampling techniques 2 Identify nonprobability sampling techniques 3 Evaluate sample size issues 4 Explain sources of error in survey samples 5
Populations & Samples
Set of all units Population
Subset of a population Sample
6
7
List of population members
Sampling frame
Sampling Techniques
Saturation Sampling: survey everyone (census)
Probability Sampling Participants are randomly selected
12
Closed populations Simple random
Systematic
Stratified
Cluster
Open populations Intercept
Prerecruited panel
Simple random: every member has an equal chance of being selected
Systematic: select first person at random, then select every nth person
Stratified: select random samples within population subgroups
Group A Group B Group C
Cluster: randomly select preexisting groups— everyone in selected group is surveyed
Intercept: interrupt browsing, invite every nth visitor to respond
Prerecrutited panel: randomly select members who have previously agreed to participate
Nonprobability Sampling Participants are NOT randomly selected
20
Convenience: surveyor selects handy group
21
Volunteer opt-in: Participants self-select into the sample
Snowball: participants refer associates
How large should the sample be
When using simple random
samples
Margin of Error
90% Confidence
Level
95% Confidence
Level
99% Confidence
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
When using nonprobability
samples
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
Sources of
Coverage error: sampling frame doesn’t represent population
Nonresponse error: some selected members choose not to participate
Sampling error: difference (due to chance) between sample statistic and population parameter
Summary
33
Choose sampling technique:
probability or nonprobability
Determine sample
size
Evaluate sources of
error
Selecting samples from populations
Coverage error Nonresponse error
Sampling error
Probability Simple random Systematic Stratified Cluster Intercept Prerecruited panel
Nonprobability Convenience Volunteer Snowball