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14-3 The Nature of Sampling Population Population Element Sampling Frame Census SampleTRANSCRIPT
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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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14-2
Learning Objectives
Understand . . .The accuracy and precision for
measuring sample validity.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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14-3
The Nature of Sampling
PopulationPopulation ElementSampling FrameCensusSample
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14-4
Why Sample?
Greater accuracy
Availability of elements
Greater speed
Sampling provides
Lower cost
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14-5
When Is a Census Appropriate?
NecessaryFeasible
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14-6
What Is a Valid Sample?
Accurate Precise
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14-7
Sampling Design within the Research Process
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14-8
Types of Sampling Designs
Probability Nonprobability
• Simple random • Convenience• Systematic Random • Judgement• Cluster• Stratified
• Quota• Snowball
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14-9
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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14-10
When to Use Larger Sample?
Desired precision
Number of subgroups
Confidence level
Population variance
Small error range
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14-11
Simple Random
AdvantagesEasy to implement with random dialing
DisadvantagesRequires list of population elements
Time consumingLarger sample needed
Produces larger errors
High cost
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14-12
How to Choose a Random Sample
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14-13
Systematic
AdvantagesSimple to designEasier than simple
randomEasy 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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14-14
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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14-15
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 heterogeneous
Moderate cost
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14-16
Stratified and Cluster SamplingStratified 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
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14-17
Nonprobability Samples
Cost
Feasibility
Time
No need to generalize
Limited objectives
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14-18
Nonprobability Sampling Methods
Convenience
Judgment
Quota
Snowball
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14-19
Sample Size 19
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14-20
Key Terms
CensusCluster samplingConvenience
samplingstratified samplingJudgment sampling
Nonprobability sampling
PopulationPopulation elementProbability
sampling
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14-21
Key Terms
Quota samplingSamplingSampling errorSampling frame
Simple random sample
Skip intervalSnowball samplingStratified random
samplingSystematic
sampling