1. Basic Sampling Issues

2. 1. To understand the concept of sampling.
Learning Objectives
1. To understand the concept of sampling.
2. To learn the steps in developing a sampling plan.
3. To understand the concepts of sampling error and nonsampling error.
4. To understand the differences between probability samples, and nonprobability samples.
5. To understand sampling implications of surveying over the Internet.
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3. To understand the concept of sampling.
Sampling Defined:
The process of obtaining information from a subset of a larger group.
A market researcher takes the results from the sample to make estimates of the larger group.
Sampling a small percentage of a population can result in very accurate estimates.
The sample must be selected in a scientific manner to ensure that it is representative of the population from which it was selected
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4. To understand the concept of sampling.
Population or Universe
The population or population of interest is the total group of people from whom information is needed.
Defining the population of interest is the first step in the sampling process
Requires good logic and judgment
Based on the characteristics of current or target customer
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5. To understand the concept of sampling.
Sample versus Census
Census: Data about every member of the population.
Sample: A subset of the population
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6. Exhibit 12.1 Developing a Sample Plan
Step 7.
Execute Operational Plan
Step 2. Choose
Data Collection Method
Step1.
Define the Population of Interest
Step 6. Develop Operational Plan
Step 3.
Choose Sampling Frame
Step 5. Determine Sample Size
Step 4.
Select a Sampling Method
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7. To learn the steps in developing a sample plan.
Sampling Plan
To learn the steps in developing a sample plan.
Step One: Defining the Population of Interest
Some basis for defining the population of interest.
Create Screening questions to eliminate individuals who do not belong in the population of interest
Also define the characteristics of those that should be excluded.
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8. To learn the steps in developing a sample plan.
Sampling Plan
To learn the steps in developing a sample plan.
Step Two: Choose Data Collection Method
Data collection methods have implications for the sampling process
Step Three: Choosing Sampling Frame
A list of elements or members from which the units to be sampled are selected
Identify the sampling frame—telephone book or random-digit dialing.
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9. Step Four: Select a Sampling Method
Developing A
Sampling Plan
To understand the differences between probability samples and nonprobability samples
Step Four: Select a Sampling Method
The selection will depend on:
The objectives of the study
The financial resources available
Time limitations
The nature of the problem
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10. Nonprobability samples
Exhibit 12-5 Classification of Sampling Methods
Sampling methods
Probability samples
Nonprobability samples
Systematic
Stratified
Convenience
Snowball
Cluster
Simple random
Judgement
Quota
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11. Step Four: Select a Sampling Method
To understand the differences between probability samples and nonprobability samples
Probability Samples
A known, nonzero probability of selection
Simple random sample
Every member of the population has a known and equal chance of being selected
The laws of probability are in effect
Allows sampling error to be calculated
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12. Step Four: Select a Sampling Method
To understand the differences between probability samples and nonprobability samples
Nonprobability Samples
Elements selected in a nonrandom manner.
Nonrandomness—selected on the basis of convenience
Purposeful nonrandomness—systematically excludes or overrepresents certain subsets of the population
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13. Step Four: Select a Sampling Method
To understand the differences between probability samples and nonprobability samples
Advantages Of Probability Samples
Information from a representative cross-section
Sampling error can be computed
Results are projectable to the total population.
Disadvantages Of Probability Samples
More expansive than nonprobabiity samples
Take more time to design and execute.
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14. Step Four: Select a Sampling Method
To understand the differences between probability samples and nonprobability samples
Disadvantages of Nonprobability Samples
Sampling error cannot be computed
Representativeness of the sample is not known
Results cannot be projected to the population.
Advantages of Nonprobability Samples
Cost less than probability
Can be conducted more quickly
Produces samples that are reasonably representative .
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15. Steps In Developing A Sampling Plan
To learn the steps in developing a sample plan.
Step Five: Determine Sample Size
Discussed more in depth in Chapter 13
Nonprobability Samples
available budget
rules of thumb
number of subgroups to be analyzed in their determination of sample size
Probability Samples
Acceptable error
Levels of confidence
The ability to make statistical inferences about population values
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16. Steps In Developing A Sampling Plan
To learn the steps in developing a sample plan.
Step Six: Develop of Operational Procedures for Selecting Sample Elements
Specify whether a probability or nonprobability sample is being used
Procedures—detailed, clear, and unambiguous
Failure to do so can jeopardize the entire sampling process
Step Seven: Execute the Sampling Plan
Requires adequate checking to ensure that specified procedures are done.
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17. Sampling And Nonsampling Errors
To understand the concepts of sampling error and nonsampling error.
Sampling Error
The error that results when the same sample is not perfectly representative of the population.
Two types of sampling error:  + - s
ns
X =
X = sample mean 
= true population mean s
= sampling error
ns
= nonsampling error
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18. Probability Sampling Methods
To understand the concepts of sampling error and nonsampling error.
Simple Random Sampling
Purest form of probability sampling
Known and equal probability is computed as follows:
Probability of selection =
Using sampling frame the researcher can select a simple random sample
Assign a number to each element of the population
Using a table of random numbers begin at some arbitrary point and move up, down, or across
Sample Size
Population Size
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19. Probability Sampling Methods
To understand the concepts of sampling error and nonsampling error.
Systematic Sampling
Uses a fixed skip interval to draw elements from a numbered population.
Skip Interval =
Obtain a listing of the population and the entire population
Determine a skip interval
Select names based on skip interval, using a random starting point
Population Size
Sample Size
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20. Probability Sampling Methods
To understand the concepts of sampling error and nonsampling error.
Stratified Samples
Probability samples that are distinguished by the following steps:
The original population is divided into two or more mutually exclusive and exhaustive subsets
Simple random samples of elements from the two or more subsets are chosen independently from each other.
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21. Probability Sampling Methods
To understand the concepts of sampling error and nonsampling error.
Three steps: In implementing a properly stratified sample:
Identify salient demographic or classification factors correlated with the behavior of interest.
Determine what proportions of the population fall into various sub subgroups under each stratum.
proportional allocation
disproportional or optimal allocation
Select separate simple random samples from each stratum
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22. Probability Sampling Methods
To understand the concepts of sampling error and nonsampling error.
Cluster Samples
Two basic steps in cluster sampling
The population of interest is divided into mutually exclusive and exhaustive subsets.
A random sample of the subsets is selected.
One-stage cluster—all elements in subset selected
Two-stage cluster—elements selected in some probabilistic manner from the selected subsets
Not individual elements
area sample—the clusters are units of geography
Main assumption—elements in cluster are heterogeneous
Clusters samples—
generally less statistically efficient than other types of probability samples
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23. Nonprobability Sampling Methods
To understand the concepts of sampling error and nonsampling error.
Convenience Samples
Easy to collect
Judgement Samples
Based on judgmental selection criteria
Quota Samples
Demographic characteristics in the same proportion as in the population
Snowball Samples
Additional respondents selected on referral from initial respondents.
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24. Advantages of Internet sampling:
To understand sampling implications of surveying over the Internet.
Advantages of Internet sampling:
Target respondents can complete the survey at their convenience
Data collection is inexpensive
The interview can be administered under software control
The survey can be completed quickly
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25. Disadvantages of Internet Interviewing
Internet Sampling
To understand sampling implications of surveying over the Internet.
Disadvantages of Internet Interviewing
users of the internet are not representative of the general population
no comprehensive and reliable source of addresses exists
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26. The Concept of Sampling Developing a Sampling Plan
SUMMARY
The Concept of Sampling
Developing a Sampling Plan
Sampling and Nonsampling Errors
Probability Sampling Methods
Nonprobability Sampling Methods
Internet Sampling
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27. The End Copyright © 2004 John Wiley & Sons, Inc.
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