Chapter 8 – Sampling (pp. 160-184)
Overall teaching objective: To introduce undergraduate criminal justice research methods
students to the probability and non-probability sampling procedures.
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Sampling is a scientific technique that allows a researcher to learn something about a
population by studying a few members, or a sample of that population.
There are numerous types of sampling.
Some sampling techniques allow researchers to predict, with some degree of accuracy,
something about a population based on what is learned from a representative sample of
that population.
Other sampling techniques merely provide researchers insight into a population.
Table 8.1 - Summary of Commonly Used Probability and Non-Probability Sampling
Techniques (p. 161)
Probability samples
Simple or Systematic random sampling
Cases are randomly selected
from a complete list of the
entire population.
Cluster sampling
The sample is collected
randomly in a series of stages
or from randomly selected
natural clusters wherein the
cases are more readily
accessible.
Stratified random sampling
Cases are selected from well
defined strata within the
overall population to further
enhance the representativeness
of the overall sample.
Non-Probability Sampling
Convenience sampling
The sample consists of
individuals that are either
convenient or readily available
to the researcher.
Snowball sampling
The sample consists of
individuals who are referred to
the researcher individually by
previous research subjects.
Typical or Extreme case sampling
Individuals or situations are
selected to be studied because
in the researcher’s judgment
they are either typical or
extreme examples.
Making Research Real 8.1 – Low Morale at the Jail (p. 160)
 A county sheriff uses a probability sampling technique (simple random sampling)
to determine the cause of low morale among the employees in a jail.
 Because the jail is a large urban jail it was not possible for the sheriff to interview
every employee.
Sampling Basics (p. 162)
 Sampling is based on a concept called the central limit theorem. The central limit
theorem gives us confidence that if we collect a large enough sample, the sample
will be representative of the larger population.
 A population is the entire set of individuals or groups that is relevant to a research
project.
 A census collects information from an entire population.
 A sample collects information from a group within that population. Samples are
typically less expensive and time-consuming than censuses.
 The terms ‘members’, ‘cases’ and ‘elements’ are used interchangeably to describe
the individual components of a population or sample.
 A list of the individual components of a population is referred to as a sampling
frame. This list enables researchers to select a subset of the population for their
sample.
 The exact process used to select the sample is called a sampling plan.
Sample Bias and Precision (p. 164)
 Random sampling error is one form of bias. It represents the difference between
the results the researcher gets from the sample and what the results might have
been had the entire population been polled. Samples from highly diverse
populations tend to have more sampling error.
 Selection bias is another form of bias. It is caused by any process that
systematically increases or decreases the chances that a member of a population
will be selected into the sample.
 A sample’s representativeness of a population is referred to as its level of
precision. The level of precision is influenced by the size of the population, the
amount of variability within the population and the frequency with which relevant
social phenomena occurs.
Making Research Real 8.2 – How Safe is Your Hamburger?(p. 165)
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A researcher attempts to develop an appropriate sampling plan for measuring the
pathogenic infestation within the nation’s meat supply.
This is an illustration (outside ‘traditional’ criminal justice) of a practical
application of sampling.
Making Research Real 8.3 – It’s Just a Simple Telephone Survey (p. 166)
 The students in Professor Jackson’s class attempt to collect a sample residents to
interview.
 The professor notices a bias in the sampling plan that causes older residents to be
more likely to be included in the sample.
Making Research Real 8.4 – Predicting the Outcome of the Public Bond Election (p. 167)
 Although not criminal justice per se, a practitioner may be interested in using a
sample
 This case illustrates the function of sampling precision
Probability Sampling Techniques (p. 168)
 Probability sampling is a general type of sampling that relies on random selection.
 Random selection means that each member of a population has an equal and nonzero chance of being selected into the sample.
 In simple random sampling, a researcher randomly selects cases into a sample
directly from a population, similar to drawing names out of a hat.
 In systematic random sampling, a researcher uses a structured process to
randomly select cases into a sample. For example, the researcher might select
every tenth case from the population.
 In cluster sampling, researchers identify natural groupings (i.e., clusters) that exist
within the population. Some of these natural groupings are randomly selected in
the initial stage of the sampling process. Cases are then randomly selected from
the chosen clusters until an appropriate sized sample has been reached. Cluster
sampling is a type of multi-stage sampling because it involves multiple stages in
the random selection process.
 Stratified random sampling is a multi-stage probability sampling technique that
involves randomly selecting cases from groups created within the population.
These groups, called strata, are defined by the researcher. This form of
probability sampling helps researchers insure the sample will be representative of
the overall population.
Making Research Real 8.5 – A Survey of Probationers (p. 170)
 This story illustrates the use of a cluster sampling technique to overcome the lack
of a comprehensive (statewide) list of probationers.
 The researcher randomly selects individual probation departments and then
selects probationers from each of these departments.
Making Research Real 8.6 – Measuring Binge Drinking (p. 172)
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This story illustrates the use of a stratified sampling technique to insure that the
sample includes (proportionately) all grade levels (freshmen, sophomores,
juniors, seniors and graduate students).
The strata are the grade levels and a random sample of cases were selected from
each strata.
Non-Probability Sampling Techniques (p. 173)
 Non-probability sampling techniques do not rely on random selection and
therefore do not allow a researcher to use the sample to predict what might be
happening in the larger population.
 Even so, non-probability samples can provide in-depth information on a
population that might not otherwise be accessible and/or information that can be
used to develop theories about various phenomena.
 Convenience samples, also known as availability samples, are created when a
researcher selects a sample from a group of people who are at hand or easily
available. Normally, researchers rely upon their own experience and judgment
when creating a convenience sample.
 Snowball sampling is a non-probability sampling technique that relies on the
sample members themselves to increase the sample size. Members recruited into
the sample identify other members of the population and refer the researcher to
these contacts until the sample ‘snowballs’ in size.
 Typical and extreme case samples consist of a single case study of a population or
phenomenon. In a typical case sample, a researcher uses a case study to illustrate
a common or typical pattern. In an extreme case sample, a researcher uses a case
study to illustrate an uncommon or atypical pattern.
Making Research Real 8.7 – What is Life Like for an Undocumented Immigrant? (p. 175)
 A police chief draws a convenience sample of undocumented immigrants to study
how they live and negotiate life without benefit of citizenship.
 He draws his sample from church membership rolls.
Making Research Real 8.8 – The Prostitute Study (p. 176)
 Because there is no definitive list of prostitutes (i.e. a sampling frame) are
researcher chooses to collect a non-probability sample.
 He is interested in them because of an increase in admissions to hospitals of
prostitutes overdosing on a new form of illicit narcotic.
 He uses a snowball sampling technique to find prostitutes to interview and asks
them about a new form of drug use among their peers.
Making Research Real 8.9 – What Happened to Sally May? (p. 178)
 A researcher uses an extreme case study approach to study what happened to a
girl who was murdered by her non-custodial parent.
 This study revealed inconsistencies and lapses in the state’s child welfare system.
Getting to the Point (Chapter Summary) (p. 179)
o Sampling is a scientific technique that allows a researcher to learn something
about a population by studying only a few members of the population.
o Sampling is based on a concept called the central limit theorem. The central limit
theorem gives us confidence that if we collect a large enough sample, the sample
will be representative of the larger population.
o A population is the entire set of individuals or groups that is relevant to a research
project. A census collects information from an entire population. A sample
collects information from a group within that population. Samples are typically
less expensive and time-consuming than censuses.
o The terms ‘members’, ‘cases’ and ‘elements’ are used interchangeably to describe
the individual components of a population or sample. A list of the individual
components of a population is referred to as a sampling frame. This list enables
researchers to select a subset of the population for their sample. The exact
process used to select the sample is called a sampling plan.
o Random sampling error is one form of bias. It represents the difference between
the results the researcher gets from the sample and what the results might have
been had the entire population been polled. Samples from highly diverse
populations tend to have more sampling error.
o Selection bias is another form of bias. It is caused by any process that
systematically increases or decreases the chances that a member of a population
will be selected into the sample.
o A sample’s representativeness of a population is referred to as its level of
precision. The level of precision is influenced by the size of the population, the
amount of variability within the population and the frequency with which relevant
social phenomena occurs.
o Probability sampling is a general type of sampling that relies on random selection.
Random selection means that each member of a population has an equal and nonzero chance of being selected into the sample.
o In simple random sampling, a researcher randomly selects cases into a sample
directly from a population, similar to drawing names out of a hat. In systematic
random sampling, a researcher uses a structured process to randomly select cases
into a sample. For example, the researcher might select every tenth case from the
population.
o In cluster sampling, researchers identify natural groupings (i.e., clusters) that exist
within the population. Some of these natural groupings are randomly selected in
the initial stage of the sampling process. Cases are then randomly selected from
the chosen clusters until an appropriate sized sample has been reached. Cluster
sampling is a type of multi-stage sampling because it involves multiple stages in
the random selection process.

Stratified random sampling is a multi-stage probability sampling technique that involves
randomly selecting cases from groups created within the population. These groups,
called strata, are defined by the researcher. This form of probability sampling helps
researchers insure the sample will be representative of the overall population.

Non-probability sampling techniques do not rely on random selection and therefore do
not allow a researcher to use the sample to predict what might be happening in the larger
population. Even so, non-probability samples can provide in-depth information on a
population that might not otherwise be accessible and/or information that can be used to
develop theories about various phenomena.

Convenience samples, also known as availability samples, are created when a researcher
selects a sample from a group of people who are at hand or easily available. Normally,
researchers rely upon their own experience and judgment when creating a convenience
sample.

Snowball sampling is a non-probability sampling technique that relies on the sample
members themselves to increase the sample size. Members recruited into the sample
identify other members of the population and refer the researcher to these contacts until
the sample ‘snowballs’ in size.

Typical and extreme case samples consist of a single case study of a population or
phenomenon. In a typical case sample, a researcher uses a case study to illustrate a
common or typical pattern. In an extreme case sample, a researcher uses a case study to
illustrate an uncommon or atypical pattern.