Social Research Methods: Qualitative and Quantitative Approaches

QUALITATIVE AND QUANTITATIVE SAMPLING

Before you move on, it may be useful to restate
a fundamental principle of all social research: Do
not compartmentalize the steps of the research pro-
cess; rather, learn to see the interconnections among
the steps. Research design, measurement, sampling,
and specific research techniques are interdepend-
ent. In practice, we need to think about data collec-
tion as we design research and develop measures.

Likewise, sampling issues influence research

design, measurement, and data collection strategies.

As you will see, good social research depends on

simultaneously controlling quality at several differ-

ent steps: research design, conceptualization, mea-

surement, sampling, and data collection and

handling. Making serious errors at any one stage

could make an entire research project worthless.

KEY TERMS

adaptive sampling
central limit theorem
cluster sampling
confidence intervals
convenience sampling
deviant case sampling
hidden populations
parameter
population
probability proportionate to
size (PPS)

purposive sampling

quota sampling

random-digit dialing (RDD)

random-number table

random sample

sample

sampling distribution

sampling element

sampling error

sampling frame

sampling interval

sampling ratio

sequential sampling

simple random sample

snowball sampling

statistic

stratified sampling

systematic sampling

target population

theoretical sampling

REVIEW QUESTIONS

1.When is purposive sampling used?

2.When is the snowball sampling technique appropriate?

3.What is a sampling frame and why is it important?

4.Which sampling method is best when the population has several groups and a

researcher wants to ensure that each group is in the sample?

5.How can researchers determine a sampling interval from a sampling ratio?

6.When should a researcher consider using probability proportionate to size?

7.What is the population in random-digit dialing? Does this type avoid sampling

frame problems? Explain.

8.How do researchers decide how large a sample to use?

9.How are the logic of sampling and the logic of measurement related?

10. When is random-digit dialing used, and what are its advantages and disadvantages?