Slide 12-1 © 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e Basic Sampling Issues Carl McDaniel, Jr. Roger Gates Slides

Slide 12-1Slide 12-1© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e© 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e

Basic Sampling Issues

Carl McDaniel, Jr.

Roger Gates

Slides Prepared by

Bruce R. Barringer

University of Central Florida

Chapter 12


Learning ObjectivesLearning ObjectivesSlide 1 of 2Slide 1 of 2

• To understand the concept of sampling.

• To learn the steps in developing a sampling plan.

• To understand the differences between probability samples and nonprobability samples.

• To understand the concepts of sampling error and nonsampling error.


Learning ObjectivesLearning ObjectivesSlide 2 of 2Slide 2 of 2

• To review the types of probability sampling methods.

• To gain insight into nonprobability sampling methods.


Definitions of Important TermsDefinitions of Important Terms

• Population or Universe– The total group of people from whom

information is needed.

• Census– Data obtained from or about every member of

the population of interest.

• Sample– A subset of the population of interest.


Steps in Developing a Sample PlanSteps in Developing a Sample Plan

Step 1: Define thePopulation of

Interest

Step 1: Define thePopulation of

Interest

Step 2: ChooseData Collection

Method

Step 2: ChooseData Collection

Method

Step 3: ChooseSampling Frames

Step 3: ChooseSampling Frames

Step 4: Select aSampling Method

Step 4: Select aSampling Method

Step 5: DetermineSample Size

Step 5: DetermineSample Size

Step 6: Develop andSpecify Operational

Plan

Step 6: Develop andSpecify Operational

Plan

Step 7: ExecuteOperational Sampling

Plan

Step 7: ExecuteOperational Sampling

Plan


Steps in Developing a Sampling PlanSteps in Developing a Sampling PlanSlide 1 of 8Slide 1 of 8

• Step 1: Defining the Population of Interest– Bases for defining the population of interest

include: • Geography

• Demographics

• Use

• Awareness



• Step 2: Choosing a Data Collection Method– The selection of a data collection method has

implications for the sampling process.

• Step 3: Choosing a Sampling Frame– Sampling frame

• List of population elements from which to select units to be sampled.



• Step 4: Selecting the Sampling Method– Probability samples

• Samples in which every element of the population has a known, nonzero probability of selection.

– Nonprobability samples• Include the selection of specific elements from the

population in a nonrandom manner.



• Step 4: Selecting the Sampling Method (continued)– Sampling error: The difference between the

sample value and the true value of the population mean.



Advantages of probability samples

Disadvantages of probability samples

- The researcher can be sure of obtaining information from a representative cross section of the population of interest.

- Sampling error can be computed.

- The survey results are projectable to the total population.

- They are more expensive than nonprobability samples of the same size in most cases. The rules for selection increase interviewing costs and professional time must be spent in developing the sample design.

- Probability samples take more time to design and execute than nonprobability samples.



Advantages of nonprobability samples

Disadvantages of nonprobability samples

- Nonprobability samples cost less than probability samples. This characteristic of nonprobability samples may have considerable appeal in those situations where accuracy is not of critical importance.

- Nonprobability samples ordinarily can be conducted more quickly than probability samples.

- - Sampling error cannot be computed.

- The researcher does not know the degree to which the sample is representative of the population from which it was drawn, but can draw inferences.

- The results of nonprobability samples cannot and should not be projected to the total population; this is not true in all cases.



• Step 5: Determine Sample Size– Once the sampling method has been chosen, the

next step is to determine the appropriate sample size.

• Step 6: Developing Operational Procedures for Selecting Sample Elements– Involves determining whether a probability or

nonprobability sample is being used.



• Step 7: Execution of the Sampling Plan– The final step in the sampling process involves

execution of the operational sampling plan discussed in the previous steps.

– It is important that this step include adequate checking to make sure that specified procedures are adhered to.


Classification of Sampling MethodsClassification of Sampling Methods

SamplingMethodsSamplingMethods

ProbabilitySamples

ProbabilitySamples

SimpleRandomSimple

RandomClusterCluster

SystematicSystematic StratifiedStratified

Non-probability

Non-probability

QuotaQuotaJudgmentJudgment

ConvenienceConvenience SnowballSnowball


Probability Sampling MethodsProbability Sampling MethodsSlide 1 of 4Slide 1 of 4

• Simple Random Sampling– Is considered to be the purest form of

probability sampling. A probability sample is a sample in which every element of the population has a known and equal probability of being selected into the sample.

Probability of Selection = Sample Size

Population Size



• Systematic Sampling– Probability sampling in which the entire

population is numbered, and elements are drawn using a skip interval.

Skip Interval = Population Size

Sample Size



• Stratified Samples– Stratified samples are probability samples that are

distinguished by the following procedural steps:• First, the original or parent population is divided into

two or more mutually exclusive and exhaustive subsets (e.g., male and female).

• Second, simple random samples of elements from the two or more subsets are chosen independently from each other, either proportionately or disproportionately.



• Cluster Samples– In the case of cluster samples, the sampling

units are selected in groups. There are two basic steps in cluster sampling:

• First, the population of interest is divided into mutually exclusive and exhaustive subsets.

• Second, a random sample of the subsets is selected.


Nonprobability Sampling MethodsNonprobability Sampling MethodsSlide 1 of 3Slide 1 of 3

• Convenience Samples– Nonprobability samples used primarily because

they are easy to collect.

• Judgment Samples– Nonprobability samples in which the selection

criteria are based on personal judgment that the element is representative of the population under study.



• Quota Samples– Nonprobability samples in which population

subgroups are classified on the basis of researcher judgment.

• Snowball Samples– Nonprobability samples in which selection of

additional respondents is based on referrals from the initial respondents.



• Convenience Samples– Nonprobability samples used primarily because

they are easy to collect.

• Judgment Samples– Nonprobability samples in which the selection

criteria are based on personal judgment that the element is representative of the population under study.


Summary of Key PointsSummary of Key PointsSlide 1 of 2Slide 1 of 2

• The population, or universe, is the total group of people in whose opinions one is interested.

• A census involves collecting desired information from all the members of the population of interest.

• A sample is simply a subset of a population.


Summary of Key PointsSummary of Key PointsSlide 2 of 2Slide 2 of 2

• Probability sampling methods are selected in such a way that every element of the population has a known, nonzero probability of selection.

• Nonprobability sampling methods include all methods that select specific elements from the population in a nonrandom manner.

Documents

Slide 12-1 © 1999 South-Western Publishing McDaniel Gates Contemporary Marketing Research, 4e Basic Sampling Issues Carl McDaniel, Jr. Roger Gates Slides