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 . . . - PowerPoint PPT PresentationTRANSCRIPT
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McGraw-Hill/Irwin Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved.
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
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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.
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McGraw-Hill/Irwin Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved.
SAMPLING
Chapter 14
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Photo AttributionsSlide Source
5 ©Ocean/Corbis9 Chris Satttlberger/Getty Images
12 Jochen Sands/Getty Images 13 Getty Images15 KidStock/Getty Images
23 Ryan McVay/Getty Images24 Photodisc/Getty Images28 David and Les Jacobs/Blend Images