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Chapter 10
Sampling: Theories, Designs
and Plans
Chapter 10
Sampling: Theories, Designs
and Plans
Sampling Terms
• Sampling - selecting a small number of elements (sample) from a larger defined group (population).
• Census - data is collected from every member of the target population.
• Sampling - selecting a small number of elements (sample) from a larger defined group (population).
• Census - data is collected from every member of the target population.
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Population – everyone in the universe
Elements – specific units of interest in the population.(They can be people, products, stores, etc.)
Defined target population – population of interest in the study
Sampling units – individual elements chosen in the sample
Sampling frame – list of potential population elements
Other Sampling Terms
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Sampling Error – any type of bias that results from
mistakes in either the selection process of sampling units or in determining the sample size.http://www.statcan.ca/english/edu/power/ch6/sampling/sampling.htm#samplesize
Sampling Error – any type of bias that results from mistakes in either the selection process of
sampling units or in determining the sample size.http://www.statcan.ca/english/edu/power/ch6/sampling/sampling.htm#samplesize
Types of Errors
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Nonsampling Error – bias that occurs in a research study regardless of whether a sample or census is used; e.g., bias caused by measurement errors,
response errors, coding errors, etc.
Nonsampling Error – bias that occurs in a research study regardless of whether a sample or census is used; e.g., bias caused by measurement errors,
response errors, coding errors, etc.
Probability Simple random Systematic random Stratified random Cluster sampling
Nonprobability Convenience
sampling Judgment sampling Quota sampling Snowball sampling
Types of Sampling Methods
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1. Obtain a list of units that contains an acceptable frame of the target population.
2. Determine the number of units in the list and the desired sample size.
3. Compute the skip interval.4. Determine a random start point.5. Beginning at the start point,
select the units by choosing each unit that corresponds to the skip interval.
Steps in Drawing a Systematic Random Sample
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Selecting a Stratified Random Sample – Three Basic Steps –
(3) Combine samples from each stratum into a
single sample.
(3) Combine samples from each stratum into a
single sample.
(2) Select random samples from each
stratum.
(2) Select random samples from each
stratum.
(1) Divide population into homogeneous
subgroups.
(1) Divide population into homogeneous
subgroups.
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1. Identify target population and determine
clustering factors. (people type, store type, etc).
2. Determine the number of units in each cluster.
3. Determine the number of units in each cluster are needed to represent the cluster.
4. Randomly select units within each cluster.
5. Combine cluster samples into one study sample.
Different than stratified because of the increased need for knowledge of the population and cluster groups to be able to accurately complete it.
Steps in Drawing a Cluster Sample
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Factors to Consider in Sample
Design
Research objectivesResearch objectives Degree of accuracyDegree of accuracy
ResourcesResources Time frameTime frame
Knowledge abouttarget population
Knowledge abouttarget population Research scopeResearch scope
Statistical analysis requirementsStatistical analysis requirements
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Variability of the population characteristic under investigation.
Level of confidence desired in the estimate, most often 95% (within 2 SD).
Degree of precision desired in estimating the population characteristic, e.g. sampling error = +/- 2.
Other . . . o Formulaso Rules of Thumb
Factors Affecting Sample Size
http://www.surveysystem.com/sscalc.htm Sample Size Calculator
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1. Define the Target Population
2. Select the Data Collection Method
3. Identify the Sampling Frame(s) Needed
4. Identify the Appropriate Sampling Method
5. Determine Sample Sizes and Contact Rates
6. Create Plan for Selecting Sampling Units
7. Execute the Plan
Steps in Developing a Sampling Plan
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