Chapter 14

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SAMPLING

Chapter 14

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Learning Objectives

Understand . . .The two premises on which sampling

theory is based.The accuracy and precision for

measuring sample validity.The five questions that must be

answered to develop a sampling plan.

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Learning Objectives

Understand . . . The two categories of sampling

techniques and the variety of sampling techniques within each category.

The various sampling techniques and when each is used.

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Pull Quote

“We have to hear what’s being said in a natural environment, and social media is an obvious place to do this, but we also have to go and discover the opinions that are not being openly shared. Only then can we understand the dichotomy between the public and private persona.”

Ben Leet, sales directoruSamp

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The Nature of Sampling

Population Population Element Sampling Frame Census Sample

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Why Sample?

Greater accuracy

Availability of elements

Greater speed

Sampling provides

Lower cost

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What Is a Sufficiently Large Sample?

“In recent Gallup ‘Poll on polls,’ . . . When asked about the scientific sampling foundation on which polls are based . . . most said that a survey of 1,500 – 2,000 respondents—a larger than average sample size for national polls—cannot represent the views of all Americans.”

Frank Newport The Gallup Poll editor in chief

The Gallup Organization

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When Is a Census Appropriate?

NecessaryFeasible

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What Is a Valid Sample?

Accurate Precise

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Sampling Design within the Research Process

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Types of Sampling Designs

Element Selection

Probability Nonprobability

•Unrestricted • Simple random • Convenience•Restricted • Complex random • Purposive

• Systematic • Judgment•Cluster •Quota•Stratified •Snowball•Double

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Steps in Sampling Design

What is the target population?

What are the parameters of interest?

What is the sampling frame?

What is the appropriate sampling method?

What size sample is needed?

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When to Use Larger Sample?

Desired precision

Number of subgroups

Confidence level

Population variance

Small error range

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Simple Random

Advantages Easy to implement with random dialing

DisadvantagesRequires list of population elements

Time consumingLarger sample needed

Produces larger errors

High cost

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Sample Frame

List of elements in population

Complete and correct

Error rate increases over time

May include elements that must be screened out

International frames most problematic

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How to Choose a Random Sample

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Systematic

AdvantagesSimple to designEasier than simple random

Easy to determine sampling distribution of mean or proportion

DisadvantagesPeriodicity within population may skew sample and results

Trends in list may bias results

Moderate cost

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Stratified

AdvantagesControl of sample size

in strataIncreased statistical

efficiencyProvides data to

represent and analyze subgroups

Enables use of different methods in strata

DisadvantagesIncreased error if

subgroups are selected at different rates

Especially expensive if strata on population must be created

High cost

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Cluster

AdvantagesProvides an unbiased

estimate of population parameters if properly done

Economically more efficient than simple random

Lowest cost per sample

Easy to do without list

DisadvantagesOften lower statistical

efficiency due to subgroups being homogeneous rather

than heterogeneousModerate cost

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Stratified and Cluster SamplingStratifiedPopulation divided

into few subgroupsHomogeneity within

subgroupsHeterogeneity

between subgroupsChoice of elements

from within each subgroup

ClusterPopulation divided

into many subgroupsHeterogeneity within

subgroupsHomogeneity

between subgroupsRandom choice of

subgroups

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Area Sampling

Well defined political or geographical boundaries

Low cost

Frequently used

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Double Sampling

AdvantagesMay reduce costs if

first stage results in enough data to stratify or cluster the population

DisadvantagesIncreased costs if

discriminately used

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Nonprobability Samples

Cost

Feasibility

Time

No need to generalize

Limited objectives

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Nonprobability Sampling Methods

Convenience

Judgment

Quota

Snowball

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Key Terms

Area samplingCensusCluster samplingConvenience

samplingDisproportionate

stratified samplingDouble samplingJudgment sampling

Multiphase sampling

Nonprobability sampling

PopulationPopulation elementPopulation

parametersPopulation

proportion of incidence

Probability sampling

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Key Terms

Proportionate stratified sampling

Quota samplingSample statisticsSamplingSampling errorSampling frameSequential

sampling

Simple random sample

Skip intervalSnowball samplingStratified random

samplingSystematic

samplingSystematic

variance

McGraw-Hill/Irwin Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved.

ADDITIONAL DISCUSSION OPPORTUNITIESChapter 14

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Snapshot: Ford’s New Sample

Dealers control 75% of advertising

Recruited 30 influential dealers

Morpace conducted focus groups

72-hour marathon of questions

Gave voice to important group

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Snapshot: Research for Good

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PicProfile: Mixed-Access Sampling

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CloseUp: Keynote Experiment

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CloseUp: Keynote Experiment (cont.)

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Pull Quote

“The proof of the pudding is in the eating. By a small sample we may judge of the whole piece.”

Miguel de Cervantes Saavedra author

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PulsePoint: Research Revelation

80 The average number of text messages sent per day by American teens.

McGraw-Hill/Irwin Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved.

SAMPLING

Chapter 14

14-36

Photo AttributionsSlide Source

5 ©Ocean/Corbis9 Chris Satttlberger/Getty Images

12 Jochen Sands/Getty Images 13 Getty Images15 KidStock/Getty Images

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