Transcript The Practice of Social Research

Foundations of Sociological Inquiry
The Logic of Sampling
Today’s Objectives






History of Sampling
Nonprobability Sampling
Probability Sampling
Populations and Sampling Frames
Sampling Designs
Multistage Cluster Sampling
History of Sampling



Unemployment
Politics
Poverty
In the past week were you employed?
1.
2.
Yes
No
53%
47%
1
2
Please answer ONLY if you are working or
looking for work.
In the past week were you employed?
1.
2.
Yes
No
81%
19%
1
2
Nonprobability Sampling

any technique in which samples are selected in
some way not suggested by probability theory.




Available subjects
Purposive sampling
Snowball sampling
Quota sampling
In her research project, Ella wants to study the processes
involved in lesbian partners adopting children. She starts
off by interviewing lesbian couples who have adopted in the
past, and they in turn, give her names of other lesbian
couples who have adopted.
The process by which Ella
94%
gets her sample is called
1.
2.
3.
4.
5.
quota sampling.
convenient sampling.
snowball sampling.
systematic sampling.
judgmental sampling.
2%
1
2%
2
1%
3
4
2%
5
Probability Sampling

the general term for samples selected in accord with
probability theory.




Often used for large-scale surveys
Also used for other types of quantitative data
collection/analysis
A sample of observations from a population must contain
the same variations that exist in the population
(representative)
A sample will be representative of the population from
which it is selected if all members/elements of the
population have an equal chance of being selected in the
sample
A _______ is the list of elements from which
a probability sample is selected.
1.
2.
3.
4.
confidence interval
confidence level
sampling frame
systematic sample
70%
14%
11%
5%
1
2
3
4
Populations and Sampling Frames


Population – the theoretically specified aggregation
of the elements in a study
Sampling Frame – a list of units that compose a
population from which a sample is selected.
Research suggests that samples of
respondents drawn from people living in
households are:
1.
2.
3.
More likely to be
employed than those
not living in
households
Less likely to be
employed than those
not living in
households
I don’t know
74%
20%
5%
1
2
3
Populations and Sampling Frames

Statistics can be used to:


Summarize the characteristics of the sample
(summary)
Estimate population parameters (inference)
 Frequentist
(assumes the population is known, or at
least from a known distribution, to make statements of
inference/uncertainty)
 Bayesian (uses the observed data to generate
statements of inference/uncertainty)
A summary description of a variable in a
sample is called a
1.
2.
3.
4.
5.
variable.
parameter.
confidence level.
confidence interval.
statistic.
54%
34%
9%
2%
1
2
3
1%
4
5
Populations and Sampling Frames


Sampling Error – the degree of error to be expected
of a given sample design.
Confidence Levels and Confidence Intervals


Confidence Level – the estimated probability that a
population parameter lies within a given confidence
interval.
Confidence Interval – the range of values within which a
population parameter is estimated to lie.
_____ of people fall within TWO standard
deviations of a normal distribution.
1.
2.
3.
4.
5.
68%
90%
95%
99.7%
34%
0%
1
0%
2
0%
0%
3
4
0%
5
Sampling Designs

Simple Random Sampling


Systematic Sampling


a type of probability sampling in which every kth unit in a list is
selected for inclusion in the sample.
Stratified Sampling


a type of probability sampling in which the units composing a
population are assigned numbers. A set of random numbers is
generated and the units having those numbers are included in the
sample.
Stratification – the grouping of units composing a population into
homogenous groups (strata) before sampling
Implicit Stratification in Systematic Sampling

a multistage sampling in which natural groups are sampled initially
with the members of each selected group being sub-sampled
afterward.
You are doing research on hospital personnel—orderlies,
technicians, nurses, and doctors. You want to be sure you
draw a sample that has cases in each of the personnel
categories. You want to use probability sampling. An
appropriate strategy would be
1.
2.
3.
4.
5.
simple random
sampling.
quota sampling.
cluster sampling.
stratified sampling.
accidental sampling.
0%
1
0%
2
0%
0%
3
4
0%
5
Which of the following statements about stratifying
a population prior to drawing a sample is TRUE?
1.
2.
3.
4.
5.
Stratifying a population prior to
drawing a sample eliminates the
need for simple random sampling.
Stratifying a population prior to
drawing a sample is most useful
for studying a homogeneous
population.
Stratifying a population prior to
drawing a sample eliminates the
need for probability sampling.
Stratifying a population prior to
drawing a sample is an alternative
to either random or systematic
sampling.
All of these statements are
FALSE.
0%
1
0%
2
0%
0%
3
4
0%
5
Cluster sampling may be used when it is
impossible to compile an exhaustive list of
the elements composing the target
population.
1.
2.
True
False
0%
1
0%
2
Questions?