Chapter 14
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Chapter 14. Sampling. 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. Learning Objectives. Understand . . .

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Chapter 14

Chapter 14

Sampling


Learning objectives

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.


Learning objectives1

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.


Pull quote

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 director

uSamp


The nature of sampling

Population

Population Element

Sampling Frame

Census

Sample

The Nature of Sampling


Why sample

Greater speed

Why Sample?

Lower cost

Availability of elements

Sampling

provides

Greater accuracy


What is a sufficiently large sample

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


When is a census appropriate

When Is a Census Appropriate?

Feasible

Necessary


What is a valid sample

What Is a Valid Sample?

Accurate

Precise


Sampling design within the research process

Sampling Design within the Research Process


Types of sampling designs

Types of Sampling Designs


Steps in sampling design

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?


When to use larger sample

Population variance

Desired precision

Number of subgroups

Confidence level

Small error range

When to Use Larger Sample?


Simple random

Simple Random

Advantages

  • Easy to implement

    with random dialing

Disadvantages

  • Requires list of population elements

  • Time consuming

  • Larger sample needed

  • Produces larger errors

  • High cost


Sample frame

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


How to choose a random sample

How to Choose a Random Sample


Systematic

Systematic

Advantages

  • Simple to design

  • Easier than simple random

  • Easy to determine sampling distribution of mean or proportion

Disadvantages

  • Periodicity within population may skew sample and results

  • Trends in list may bias results

  • Moderate cost


Stratified

Stratified

Advantages

  • Control of sample size in strata

  • Increased statistical efficiency

  • Provides data to represent and analyze subgroups

  • Enables use of different methods in strata

Disadvantages

  • Increased error if subgroups are selected at different rates

  • Especially expensive if strata on population must be created

  • High cost


Cluster

Cluster

Advantages

  • Provides an unbiased estimate of population parameters if properly done

  • Economically more efficient than simple random

  • Lowest cost per sample

  • Easy to do without list

Disadvantages

  • Often lower statistical efficiency due to subgroups being homogeneous rather than heterogeneous

  • Moderate cost


Stratified and cluster sampling

Stratified and Cluster Sampling

Stratified

  • Population divided into few subgroups

  • Homogeneity within subgroups

  • Heterogeneity between subgroups

  • Choice of elements from within each subgroup

Cluster

  • Population divided into many subgroups

  • Heterogeneity within subgroups

  • Homogeneity between subgroups

  • Random choice of subgroups


Area sampling

Area Sampling

Well defined political or

geographical boundaries

Low cost

Frequently used


Double sampling

Double Sampling

Advantages

  • May reduce costs if first stage results in enough data to stratify or cluster the population

Disadvantages

  • Increased costs if discriminately used


Nonprobability samples

Time

Nonprobability Samples

No need to generalize

Feasibility

Limited objectives

Cost


Nonprobability sampling methods

Nonprobability Sampling Methods

Convenience

Judgment

Quota

Snowball


Key terms

Key Terms

  • Area sampling

  • Census

  • Cluster sampling

  • Convenience sampling

  • Disproportionate stratified sampling

  • Double sampling

  • Judgment sampling

  • Multiphase sampling

  • Nonprobability sampling

  • Population

  • Population element

  • Population parameters

  • Population proportion of incidence

  • Probability sampling


Key terms1

Key Terms

  • Proportionate stratified sampling

  • Quota sampling

  • Sample statistics

  • Sampling

  • Sampling error

  • Sampling frame

  • Sequential sampling

  • Simple random sample

  • Skip interval

  • Snowball sampling

  • Stratified random sampling

  • Systematic sampling

  • Systematic variance


Chapter 141

Chapter 14

Additional Discussion opportunities


Snapshot ford s new sample

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


Snapshot research for good

Snapshot: Research for Good


Picprofile mixed access sampling

PicProfile: Mixed-Access Sampling


Closeup keynote experiment

CloseUp: Keynote Experiment


Closeup keynote experiment cont

CloseUp: Keynote Experiment (cont.)


Pull quote1

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


Pulsepoint research revelation

PulsePoint: Research Revelation

80

The average number of text messages sent per day by

American teens.


Chapter 142

Chapter 14

Sampling


Photo attributions

Photo Attributions


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