2. Why Sample?
Why not everyone?

3. Sampling
A process used in statistical
analysis in which a
predetermined number of
observations will be taken
from a larger population

4. The Sampling Design Process
Define the Population
Determine the Sampling Frame
Select Sampling Technique(s)
Determine the Sample Size
Execute the Sampling Process

5. Key sampling concepts

7. Key ideas

8. Sampling frame

9. Classification of Sampling
Techniques
Sampling Techniques
Nonprobability Probability
Sampling Techniques Sampling Techniques
Convenience Judgmental Quota Snowball
Sampling Sampling Sampling Sampling
Simple Systematic Stratified Cluster Other Sampling
Random Sampling Sampling Sampling Techniques
Sampling

10. Convenience Sampling
Subjects are selected because they are
easily accessible.
This is one of the weakest sampling
procedures.
An example might be surveying students in
one's class.
Generalization to a population can seldom
be made with this procedure.. ………..

11. Judgmental Sampling
A form of convenience sampling in which the population elements are selected based on the
judgment of the researcher.
Test markets
Purchase engineers
selected in industrial
marketing research
Bellwether precincts
selected in voting behavior
research (Exit poll?)

12. Quota sampling
For example, an
A pre-defined interviewer
number (or quota) may be given
the task of
of people who interviewing 25
• On a weekday morning,
meet certain women with
toddlers in a
criteria are town centre
surveyed.
• Seven of these women should
be aged under 30 years,
the instructions
• Ten should be aged between
may specify
30 and 45 years,
that
• Eight should be aged over 45
years.

13. Snowball Sampling
In snowball sampling, an initial
group of respondents is selected,
usually at random.
After being interviewed, these
respondents are asked to identify
others who belong to the target
population of interest.
Subsequent respondents are
selected based on the referrals.

14. Probability samples

18. How?

22. Similarly………..

26. Cluster sampling is appropriate when it
is very time consuming or expensive to
choose the individuals one at a time

30. Multistage Sampling

31. Choosing Nonprobability vs.
Table 11.4 cont. Probability Sampling
Conditions Favoring the Use of
Factors Nonprobability Probability
sampling sampling
Nature of research Exploratory Conclusive
Relative magnitude of sampling Nonsampling Sampling
and nonsampling errors errors are errors are
larger larger
Variability in the population Homogeneous Heterogeneous
(low) (high)
Statistical considerations Unfavorable Favorable
Operational considerations Favorable Unfavorable