MGT629
Business Research
Methods
(Module 6)
Sampling Terminology
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Sample
Population or universe
Population element
Census
Sampling Methods
• Simple random sampling
• Stratified random sampling
• Cluster sampling
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Population
• Any complete group
– People
– Sales territories
– Stores
Sample
• Subset of a larger population
Census
• Investigation of all individual elements that
make up a population
Stages in the
Selection
of a Sample
Define the target population
Select a sampling frame
Determine if a probability or nonprobability
sampling method will be chosen
Plan procedure
for selecting sampling units
Determine sample size
Select actual sampling units
Conduct fieldwork
Sampling Frame
• A list of elements from which the sample may
be drawn
• Working population
• Mailing lists - data base marketers
• Sampling frame error
Random Sampling Error
• The difference between the sample results
and the result of a census conducted using
identical procedures
• Statistical fluctuation due to chance variations
Errors Associated with Sampling
• Sampling frame error
• Random sampling error
• Nonresponse error
Two Major Categories of Sampling
• Probability sampling
• Known, nonzero probability for every element
• Nonprobability sampling
• Probability of selecting any particular member
is unknown
Probability Sampling
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Simple random sample
Systematic sample
Stratified sample
Cluster sample
Multistage area sample
Simple Random Sampling
• A sampling procedure that ensures that each
element in the population will have an equal chance
of being included in the sample.
• This type of sampling is also known as chance
sampling or probability sampling where each and
every item in the population has an equal chance of
• inclusion in the sample and each one of the possible
samples, in case of finite universe, has the same
probability of being selected. For example, if we
have to select a sample of 300 items from a universe
of 15,000 items, then we can put the names or
numbers of all the
Systematic Sampling
• A simple process
• Every nth name from the list will be drawn
Stratified Sampling
• Probability sample
• Subsamples are
drawn within
different strata
• Each stratum is
more or less equal
on some
characteristic
• Do not confuse
with quota sample
Cluster Sampling
• The purpose of cluster
sampling is to sample
economically while
retaining the
characteristics of a
probability sample.
• The primary sampling unit
is no longer the individual
element in the population
• The primary sampling unit
is a larger cluster of
elements located in
proximity to one another
Cluster sampling involves grouping the population and then
selecting the groups or the clusters rather than individual
elements for inclusion in the sample.
Suppose some departmental store wishes to sample its credit
card holders.
It has issued its cards to 15,000 customers. The sample size is to
be kept say 450.
For cluster sampling this list of 15,000 card holders could be
formed into 100 clusters of 150 card holders each.
Three clusters might then be selected for the sample randomly.
The sample size must often be larger than the simple random
sample to ensure the same level of accuracy because is cluster
sampling procedural potential for order bias and other sources
of error is usually accentuated.
Nonprobability Sampling
• This is also called as Deliberate sampling: This
sampling method involves purposive or
deliberate selection of particular units of the
universe for constituting a sample which
represents the universe. When population
elements are selected for inclusion in the
sample based on the ease of access.
• Convenience
• Judgment
• Quota
• Snowball
Convenience Sampling
• Also called haphazard or accidental sampling
• The sampling procedure of obtaining the
people or units that are most conveniently
available
Judgment Sampling
• Also called purposive sampling
• An experienced individual selects the sample
based on his or her judgment about some
appropriate characteristics required of the
sample member
What is the
Appropriate Sample Design?
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Degree of accuracy
Resources
Time
Advanced knowledge of the population
National versus local
Need for statistical analysis
What does Statistics Mean?
• Descriptive statistics
– Number of people
– Trends in employment
– Data
• Inferential statistics
– Make an inference about a population from a
sample