Sampling Techniques
Every researcher wants to ensure their study provides valid, reliable, and useful results/conclusions.
We’re going to spend some time discussing the various techniques that can be used to select the
participants for a study. The ultimate goal is to obtain a representative sample of individuals from the
population of interest. The population of interest must be clearly defined before a representative
sample can be chosen.
Example: Suppose you work for a Gallup or another polling organization and are interested in predicting
who the winner of the 2012 presidential election will be. Before any data may be collected, the
population of interest must be clearly defined. What is the population of interest for a political poll?

Is the population of interest all _________________________ adults?

Is the population of interest all _________________________ voters?

Is the population of interest everyone that _______________ in the last election?
Depending on which of the above the researcher views as the population of interest will determine what
constitutes a representative sample.
Example: The Literary Digest conducted polls regarding the presidential elections in 1920, 1924, 1928,
and 1932 making correct predictions of the winner for each. In the 1936 election they decided to
conduct their most ambitious poll and collected responses from over two million people. Using this
information they predicted that Alf Landon would win the 1936 presidential election over Franklin
Roosevelt however, Franklin ended up winning the presidency with 61 percent of the votes. The Literary
Digest was left wondering what went wrong. There was also a gentleman named George Gallup who
also conducted a poll and correctly predicted the Roosevelt would win the presidency. You might
wonder what George Gallup did to end up with a correct prediction while the Literary Digest seemed to
bobble after years of correct predictions. It turns out the difference in the polls conducted was the
manner in which the samples were chosen. The Literary Digest used telephone directories and lists of
automobile owners to select their participants who consisted mostly of wealthy individuals, whereas
Gallup tried to get a sample which represented characteristics of the population. Most of the lower
class individuals voted in favor of Roosevelt because he was proposing the New Deal recovery program
which was very desirable since the country was just coming out of the worst economic recession they
had seen at the time. Source: Babbie, Earl. The Basics of Social Research. 5th Edition. Wadsworth. 2011. 204 – 205.
The key to making a correct prediction in the 1936 presidential election was the ability to get a
representative sample of the population of interest.
Representative Sample – A sample which has characteristics/properties that close approximate those of
the target population.
Before looking at some specific methods for obtaining we need a few definitions:
Observation Unit – The object on which a measurement is taken.
Example: When people are being studied, the observation units are usually individuals.
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Sampling Unit – A unit that is selected for a sample.
Example: It might not be feasible to obtain a list of all individuals in the population, but you may
be able to get a list of all households. Therefore, randomly selected households would be
chosen and the individuals living in the households would then be interviewed.
Sampling Frame – A sampling frame is a list, map or other specification of sampling units in the
population from which a sample may be selected.
Example: If one is conducting a telephone survey, the sampling frame might be the list of phone
numbers in a telephone book for a certain city. If you are conducting an agriculture survey, the
sampling frame might be a list of all farms in an area.
There are a number of different techniques which can be used to collect representative samples of
individuals to include in a study. Some of the most common techniques are:

_________________________ Random Sample (SRS)

_________________________ Random Sample

_________________________ Sample

_________________________ Sample
Next, we’ll take an in depth look at each of the above mentioned sampling techniques.
Simple Random Sample (SRS)

A simple random sample is the most _______________ form of sampling.

Definition: If a sample of size n is drawn from a population of N such that _______________
possible sample of size n has the same chance of being selected.

There are __________ possible samples of size n drawn from a population of N units. The
probability of selecting any individual sample S is _______________.
Question:
1. Decide if the following sampling methods produce a simple random sample of students from a
class of 30 students. If not, explain why.
a. Select the first six students on the class roll sheet.
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b. Pick a digit at random and select those students whose phone numbers end in that digit.
c. Randomly choose a letter from the English alphabet and select for the sample those
students whose last names begin with that letter. If no last name begins with that
letter, randomly choose another letter from the alphabet.
Stratified Random Sampling

A stratified random sample is obtained by first separating the population into _______________
groups, called strata.

Once strata have been formed, a ________ is taken from each.

Stratified random sampling is used for one or more of the following reasons:
o
To be “protected” from the possibility of obtaining a ________ sample.
Example: Suppose you have a population with an equal representation of males
and females. You may want to ensure obtaining a sample that has equal
representation since by chance you could get a sample with very few females
resulting in an underrepresentation of their opinions.
o
Want data of known precision for _________________________ of the population.
o
More ____________________ to administer and may result in a _______________ cost
for the survey.
o
Often gives more precise estimates for population __________.
Example: The Federal Deposit Insurance Corporation (FDIC) was created to
supervise banks. When a bank fails, the FDIC is acquires the bank’s assets and
uses them to help pay the insured depositors. Therefore, the FDIC must value
the assets. However, there are a number of different types of assets such as
consumer loans, commercial loans, securities, real estate mortgages, etc. If a
random sample is taken from each type of asset, it will help to ensure the FDIC
does not over or underestimate the worth.
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Questions:
2.
What stratification variable(s) would be used for each of the following situations?
a. A political poll to estimate the percentage of registered voters in Arizona that approve
of the governor’s performance.
b. An e-mail survey of students at WSU to estimate the total amount of money students
spend on textbooks in a semester.
c. A sample of high schools in Minneapolis to estimate what percentage of high schools
offer one or more computer programming classes.
3. A water management board wants to estimate the total amount of water used for irrigation in
one growing season among all farms in a certain management district. A list of farms is available
in which the farms are listed by acreage, from smallest to largest. Would you suggest using a
simple random sample or a stratified random sample of farms? Explain.
4. A researcher wants to examine the average income of employees in a large firm. Records have
employees listed by seniority, and generally speaking, salary increases with seniority. Discuss
the relative merits of simple random sampling and stratified random sampling in this case.
Which would you recommend? How would you set up the sampling scheme?
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Cluster Sampling

A cluster sample is obtained by first separating the population into _______________.

Once clusters have been formed, a _____ of _______________ is taken. Therefore, only the
units/observations in the selected clusters are used. The observations in the unselected clusters
are disregarded.

Why use cluster sampling?

o
Constructing a list of observations/units may be ___________, expensive or impossible.
o
The population of interest may be _______________ distributed graphically or may
occur in natural clusters such as households or schools.
Whereas using strata can increase precision when compared with simple random sampling,
cluster sampling generally decreases it. This is because members of the same cluster tend to be
more similar than elements selected at random from the whole population.
Questions:
5. A sociologist wants to estimate the per-capita income in a certain small city. No list of resident
adults is available. How should the researcher design the sample survey?
6. A political scientist wishes to sample resident students on a large university campus. Individual
housing units can be conveniently used as clusters of students or collections of housing units
(freshmen dormitories, fraternity houses, etc.) can be used as strata. Discuss the merits of
cluster versus stratified random sampling if the goals is to estimate the proportion of students
favoring a certain candidate in the following types of elections:
a. A student government election.
b. A national presidential election.
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Systematic Sampling

A systematic sample is obtained by first randomly selecting one element from the first _____
elements. Then every _____ observation is selected from that point on.

Systematic sampling is a useful alternative for simple random sampling for the following
reasons:
o
It is easier to perform in the field and is less subject to ____________________ errors
by fieldworkers.
o
It can provide greater ____________________ per unit cost.
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