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Chapter 6

Sampling: Theory and Methods

Learning Objectives

• Explain the role of sampling in the research process

• Distinguish between probability and nonprobability sampling

• Understand factors to consider when determining sample size

• Understand the steps in developing a sampling plan

Value of Sampling in Marketing Research

• Sampling: Selection of a small number of elements from a larger defined target group of elements

– Assumes that the information gathered from the small group helps make accurate judgments about the larger group

Sampling as a Part of the Research Process

• Sampling is used when it is impossible or unreasonable to conduct a census

– Census: Research study that includes data about every member of the defined target population

• Sampling plays an important role in designing questionnaires

– Sampling decisions influence:

• Type of survey design

• Survey instrument

Basics of Sampling Theory

• Population: Identifiable group of elements of interest to the researcher

– Pertinent to the information problem

• Defined target population: Complete set of elements identified for investigation

– Sampling units: Target population elements available for selection during the sampling process

• Sampling frame: List of all eligible sampling units

Central Limit Theorem (CLT)

• Sampling distribution derived from a simple random sample will be approximately normally distributed

• Aids in understanding concepts of:

– Sampling error

– Statistical significance

– Sample sizes

Assessing Sampling Quality

• Challenges

– Census - Seldom conducted in survey research

– Sampling error - Determined only after a sample is drawn and data collection is completed

Assessing Sample Quality

• Sampling error: Any bias attributable to mistakes in either drawing a sample or determining the sample size

• Nonsampling error: Bias that occurs in a research study regardless of whether a sample or census is used

Sampling Designs

• Probability sampling: Each sampling unit in the defined target population has a known probability of being selected for the sample

• Nonprobability sampling: Probability of selection of each sampling unit is not known

– Selection is based on the judgment of the researcher

• May or may not be representative of the target population

Types of Probability and Nonprobability Sampling Methods

Probability sampling

• Simple random sampling

• Systematic random sampling

• Stratified random sampling

• Cluster sampling

Nonprobability sampling

• Convenience sampling

• Judgment sampling

• Quota sampling

• Snowball sampling

Probability Sampling Designs

• Simple random sampling: Every sampling unit has a known and equal chance of being selected

• Systematic random sampling: Defined target population is ordered and selected systematically

– Forms - Customer list, taxpayer roll, and membership roster

Probability Sampling Designs (continued 1)

• Stratified random sampling: Separates the target population into groups or strata and selects samples from each stratum

– Proportionately stratified sampling: Each stratum is dependent on its size relative to the population

– Disproportionately stratified sampling: Size of each stratum is independent of its relative size in the population

• Optimal allocation sampling: Sample size of a stratum is determined based on its relative size and variability

Probability Sampling Designs (continued 2)

• Multisource sampling: Used when a single source cannot generate a large or low incidence sample

• Cluster sampling: Sampling units are divided into mutually exclusive and collectively exhaustive subpopulations, called clusters

– Area sampling: Clusters are formed by geographic designations

Nonprobability Sampling Methods

• Convenience sampling: Samples are drawn at the convenience of the researcher

• Judgment sampling: Participants are selected based on an experienced individual’s opinion that they will meet the study's requirements

Nonprobability Sampling Methods (continued)

• Quota sampling

– Participants are selected according to prespecified quotas regarding demographics, attitudes, behaviors, or some other criteria

• Snowball sampling: Set of chosen respondents that helps a researcher identify additional people to be included in a study

– Also called referral sampling

Exhibit 6.4 - Factors to Consider in Selecting the Sampling Design

Selection Factors Questions

Research objectives Do the research objectives call for the use of qualitative or quantitative research

designs?

Degree of accuracy Does the research call for making predictions or inferences about the defined target

population, or only preliminary insights?

Resources Are there tight budget constraints with respect to both dollars and human resources

that can be allocated to the research project?

Time frame How quickly does the research project have to be completed?

Knowledge of the target population Are there complete lists of the defined target population elements? How easy or

difficult is it to generate the required sampling frame of prospective respondents?

Scope of the research Is the research going to be international, national, regional, or local?

Statistical analysis needs To what extent are accurate statistical projections and/or testing of hypothesized

differences in the data required?

Probability Sample Sizes

• Factors that determine sample sizes with probability designs

– Population variance

– Level of confidence desired in the estimate

– Degree of precision desired in estimating the population characteristic

• Precision: Acceptable amount of error in the sample estimate

Probability Sampling and Sample Sizes

• Formula used to calculate a sample size

2( )  

    

n Z B,CL σ

– ZB,CL - Standardized z-value associated with the level of confidence

– σμ - Estimate of the population standard deviation (σ) based on some type of prior information

– e - Acceptable tolerance level of error (stated in percentage points)

Probability Sampling and Sample Sizes (continued)

• Calculating sample size when the estimates of a population proportion are of concern

     

2 B,CL 2

[ × ] = ( )

P Q n Z

– ZB,CL - Standardized z-value associated with the level of confidence

– P - Estimate of expected population proportion having a desired characteristic based on intuition or prior information

– Q - – [1 – P]

– e - Acceptable tolerance level of error

Sampling from a Small Population

• Strategy used to prevent an unnecessarily large sample size

– Calculated sample size is multiplied by the following correction factor

N/(N + n − 1)

• N - Population size

• n - Calculated sample size determined by the original formula

– Thus, Sample size=(Specified degree of confidence × Variability /Desired precision)2

× N/(N + n − 1)

Nonprobability Sample Sizes and Other Sampling Methods

• For nonprobability samples:

– Sample size formulas cannot be used

– Determining the sample size is a subjective and intuitive judgment

• Other sample size determination methods are less formal

– Basing sample size on similar previous studies

– Determining sample size on the basis of the number of questions in a questionnaire

Steps in Developing a Sampling Plan

• Blueprint or framework needed to ensure that the data collected are representative of the defined target population

• Developing a sampling plan

– Define the target population

– Select the data collection method

– Identify the sampling frames needed

– Select the appropriate sampling method

Steps in Developing a Sampling Plan (continued)

– Determine necessary sample sizes and overall contact rates

– Create an operating plan for selecting sampling units

– Execute the operational plan

Marketing Research in Action Developing a Sampling Plan for a New Menu Initiative

Survey

• How many questions should the survey contain to adequately address all possible new menu items, including the notion of assessing the desirability of new cuisines?

– How can it be determined that all necessary items will be included on the survey without the risk of ignoring menu items that may be desirable to potential customers?

Marketing Research in Action Developing a Sampling Plan for a New Menu Initiative

Survey (continued)

• How should the potential respondents be selected for the survey?

– Should customers be interviewed while they are dining?

– Should customers be asked to participate in the survey upon exiting the restaurant?

– Should a mail or telephone approach be used to collect information from customers or noncustomers?