Sampling
© 2009 University of Wisconsin-Extension, Cooperative Extension, Program Development and Evaluation
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A sample is a portion or a
subgroup of an entire
group (called the
population) from which an
estimate can be made for
the entire group.
See the booklet, Sampling
http://learningstore.uwex.edu/pdf/G3658-03.pdf
Also, see Bill Trochim’s Social Science Research Methods at
http://www.socialresearchmethods.net/kb/sampling.php
© 2009 University of Wisconsin-Extension, Cooperative Extension, Program Development and Evaluation
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Check your ‘sampling’ IQ by answering
the following questions.
1.
2.
3.
4.
5.
6.
Why do people use a sample?
Does a sample always refer to people?
Is there one best way to sample?
Should we always sample?
What makes a “good” sample?
What size does the sample need to be?
Answers follow
© 2009 University of Wisconsin-Extension, Cooperative Extension, Program Development and Evaluation
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1. Why do people use a sample?
• It is cheaper
• It can result in
more accurate data.
– Managing a representative sample to obtain a
high response rate may yield more accurate
information than surveying everyone and
having response bias.
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2. Does a sample always refer to people?
NO
You might sample
• 4-H records
• activity logs
• gardens
• demonstrations
• clubs…
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3. Is there one best way to sample?
NO
Depending upon your purpose, there are
various sampling strategies.
If you want to generalize from the sample to the
population, probability sampling is necessary.
Sometimes probability sampling is impossible
or you don’t want or need to generalize to the
larger group. Then, nonprobability sampling is
appropriate.
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Types of sampling strategies:
Probability:
• Generalize to
population.
Some examples:
– Simple random
sample
– Stratified sample
– Cluster sample
– Systematic sample
Nonprobability:
• Generalizability not as
important. Want to
focus on “right cases.”
Some examples:
– Quota sample
– “Purposeful” sample
– “Convenience” or
“opportunity” sample
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4. Should we always use a sample?
NO
• If the population is small, you may choose to
include everyone.
• If you want to be inclusive giving everyone
the chance to be involved or to know about
the issue under study, you might include
everyone.
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5. What makes a “good” sample?
When the sample accurately
represents the population.
.
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6. What size does the sample need to be?
“It all depends”… upon the size of the
population (the entire group), how varied the
population is, how much sampling error can be
tolerated, your resources.
If your purpose is to generalize or show
representativeness, then sample size is a
concern.
Use a sample size calculator to determine
sample size at different levels of precision
© 2009 University of Wisconsin-Extension, Cooperative Extension, Program Development and Evaluation
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Anticipate nonresponse
A certain number of people
will not respond for one reason or another.
Increase the sample size to account for
nonresponse.
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What do you think?
Scenario:
The local library wants to know what impact its
services are having on the community. It creates
a survey, announces the purpose and process
of the survey in the local newspaper, places the
questionnaires and locked boxes in strategic
places around the community for people to
complete and securely submit the survey, and
posts visible notices at each location to bring
attention to the survey.
© 2009 University of Wisconsin-Extension, Cooperative Extension, Program Development and Evaluation
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The previous scenario represents the
potential for sampling bias.
Bias is a systematic error that can prejudice your evaluation findings
in some way. So, sampling bias is consistent error that arises due to
the sample selection.
For example, a survey of high school students to measure teenage
use of illegal drugs will be a biased sample because it does not
include home schooled students or dropouts. A sample is also biased
if certain members are underrepresented or overrepresented relative
to others in the population. For example, distributing a questionnaire
at the end of a 3-day conference is likely to include more people who
are committed to the conference so their views would be
overrepresented. Interviews with people who walk by a certain
location is going to over-represent healthy individuals or those who
live near the location. Selecting a sample using a telephone book will
under-represent people who cannot afford a telephone, do not have a
telephone, or do not list their telephone numbers.
© 2009 University of Wisconsin-Extension, Cooperative Extension, Program Development and Evaluation
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What can you do to address
sampling bias?
Consider potential sampling bias during your
evaluation planning and correct for potential
biases.
If you do identify differences between
respondents in your sample and in the target
population, make it clear in your reporting who
the results represent.
© 2009 University of Wisconsin-Extension, Cooperative Extension, Program Development and Evaluation
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Re-check your ‘sampling’ IQ. What did
you learn? What did you already know?
What do you need more help with?
1.
2.
3.
4.
5.
6.
Why do people use a sample?
Does a sample always refer to people?
Is there one best way to sample?
Should we always sample?
What makes a “good” sample?
What size does the sample need to be?
© 2009 University of Wisconsin-Extension, Cooperative Extension, Program Development and Evaluation
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Congratulations!
We hope this presentation helped you
better understand the ins and outs of
sampling!
© 2009 University of Wisconsin-Extension, Cooperative Extension, Program Development and Evaluation
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