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Basic Sampling Issues

CHAPTER

twelve

CHAPTER

twelve

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Learning Objectives

1. To understand the concept of sampling.

2. To learn the steps in developing a sampling plan.

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

4. To distinguish between probability samples, and nonprobability samples.

5. To understand sampling implications of surveying over the Internet.

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Sampling Defined:The process of obtaining information from a subset of a larger group.

A market researcher takes the results from the sample to make estimates of the larger group.

Sampling a small percentage of a population can result in very accurate estimates.

It all depends on scientific selection.

E.g., 1,000 – 1,500 people polled to predict voting of tens of millions

To understand the concept of sampling.

The Concept of Sampling

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Population (or Universe)

The total group of people from whom we need to obtain information.

Define the target market for the product or service in question.

Sample versus Census

Census: Data about every member of the population.

Sample: A subset of the population

Definition Of Important Terms

To understand the concept of sampling.

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Step1.Define the

Population of Interest

Step 2. ChooseData Collection

Method

Step 3.Choose

Sampling Frame

(4) Select a

Sampling Method

Step 5. Determine

Sample Size

Step 6. Develop Operational Plan

Step 7.Execute

Operational Plan

Figure 12.1 Steps in Developing a Sample Plan

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Step One: Defining the Population of Interest

Specifying the characteristics from whom information is needed.

Often specify in terms of geographic area, demographics, usage, and awareness

Define the characteristics of those that should be excluded.

Use screening or security questions

To learn the steps in developing a sample plan.

Steps In Developing A Sampling Plan

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Step Two: Choose Data Collection Method

Impacts for the sampling process.

E.g., telephone interviews, internet survey, etc.

Step Three: Choosing Sampling Frame

A list of elements or members from which we select units to be sampled.

E.g., choose from phone book, or specify a procedure, such a s questionnaire, that will produce the units to be sampled.

To learn the steps in developing a sample plan.

Steps In Developing A Sampling Plan

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Name some possible sampling frames for:

1. Patrons of sushi bars

2. Smokers of high-priced cigars

3. Snowboarders

4. Owners of DVD players

5. People who have visited one or more countries in Europe in the last year

6. People with allergies

To learn the steps in developing a sample plan.

Steps In Developing A Sampling Plan

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Step Four: Select a Sampling Method

The selection will depend on:

• The objectives of the study

• The financial resources available

• Time limitations

• The nature of the problem

To learn the steps in developing a sample plan.

Steps In Developing A Sampling Plan

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Probability Samples

A known, nonzero probability of selection

Nonprobability Samples

Elements selected in a nonrandom manner (e.g., based on convenience)

To understand the steps in developing a sample plan.

Steps In Developing A Sampling Plan

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Advantages of probability samples

• Obtain information from a representative cross-section

• Sampling error can be computed.

• The survey results are projectable to the total population.

To distinguish between probability samples and nonprobability samples.

Steps In Developing A Sampling Plan

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Disadvantages of probability samples

• More expensive than nonprobability samples of the same size.

• Probability samples take more time to design and execute.

To distinguish between probability samples and nonprobability samples.

Steps In Developing A Sampling Plan

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Step Five: Determine Sample Size

For Nonprobability Samples:

• Available budget

• Rules of thumb

• Number of subgroups

For Probability Samples:

• Worry about acceptable error and levels of confidence

• See Chapter 13.

To distinguish between probability samples and nonprobability samples.

Steps In Developing A Sampling Plan

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Step Six: Develop of Operational Procedures for Selecting Sample Elements

Specify whether a probability or nonprobability sample is being used

Procedures more critical for probability sample

Step Seven: Execution the Sampling Plan

The final step of the operational sampling plan

Include adequate checking of specified procedures.

To distinguish between probability samples and nonprobability samples.

Steps In Developing A Sampling Plan

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Sampling methods

Probability samples

Systematic

Cluster

Stratified

Simple random

Nonprobability samples

Convenience

Judgment

Snowball

Quota

Figure 12.3 Classification of Sampling Methods

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Sampling ErrorThe error that results when the same sample is not perfectly representative of the population.

Two types of sampling error:

To understand the concepts of sampling error and nonsampling error.

Sampling And Nonsampling Errors

+- sns

+-X = X = sample mean

= true population mean

s = sampling error

ns = nonsampling (or measurement) error

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Sampling ErrorThe error that results when the same sample is not perfectly representative of the population.

• Administrative error: problems in the execution of the sample

• Random error: due to chance and cannot be avoided

Nonsampling (Measurement) ErrorIncludes all other factors.

To understand the concepts of sampling error and nonsampling error.

Sampling And Nonsampling Errors

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Simple Random SamplingThe purest form of probability sample

To understand the differences in probability and nonprobability sampling methods.

Probability of Selection = Sample Size

Population Size

E.g., if population size is 10,000, and sample size is 200, probability of selection is 2%.

Probability Sampling Methods

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Systematic Sampling Uses a fixed skip interval to draw elements from a

numbered population.

To understand the differences in probability and nonprobability sampling methods.

Skip Interval = Population Size

Sample Size

Probability Sampling Methods

E.g., Pick every 500th name from the phone book.

Often simpler, less time-consuming, and less expensive than simple random sampling.

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Stratified SamplesProbability samples that are distinguished by the following steps:

1. The original population is divided into two or more mutually exclusive and exhaustive subsets

2. Simple random samples of elements from the two or more subsets are chosen independently from each other.

To understand the differences in probability and nonprobability sampling methods.

Probability Sampling Methods

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Three steps involved in implementing a properly stratified sample:

1. Identify salient demographic or classification factors correlated with the behavior of interest.

2. Determine what proportions of the population fall into various sub subgroups under each stratum.

• proportional allocation• disproportional or optimal allocation

3. Select separate simple random samples from each stratum.

To understand the differences in probability and nonprobability sampling methods.

Probability Sampling Methods

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Cluster SamplesSampling units are selected in groups.

1. The population of interest is divided into mutually exclusive and exhaustive subsets.

2. A random sample of the subsets is selected.

E.g., interview everyone in a particular neighborhood (to reduce travel time and add to convenience)

To understand the differences in probability and nonprobability sampling methods.

Probability Sampling Methods

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To understand the differences in probability and nonprobability sampling methods.

Convenience Samples

Easy to collect

E.g., Ask your own employees, or rent a list of targeted people

Judgment Samples

Based on judgmental selection criteria

E.g., go to a mall to conduct taste tests.

Nonprobability Sampling Methods

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To understand the differences in probability and nonprobability sampling methods.

Quota Samples

Demographic characteristics in the same proportion as in the population

E.g., asking males questions in a mall.

Snowball Samples

Additional respondents selected on referral from initial respondents.

Good for “rare” populations, but leads to lesser sample quality.

Nonprobability Sampling Methods

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To understand sampling implications of surveying over the Internet.

Advantages of Internet sampling:

• Target respondents can complete the survey at their convenience

• Data collection is inexpensive

• The interview can be administered under software control

• The survey can be completed quickly

But…

• Not generally representative of entire population

Sampling Over the Internet

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Don’t Post Surveys in Public Areas

• Highly biased samples

• Vested interests quickly

To understand sampling implications of surveying over the Internet.

Sampling Over the Internet

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• The Concept of Sampling

• Definition Of Important Terms

• Steps In Developing A Sampling Plan

• Sampling And Nonsampling Errors

• Probability Sampling Methods

• Nonprobability Sampling Methods

• Sampling Over the Internet

SUMMARY

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The End

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