1. Learning Objectives Copyright © 2002 South-Western/Thomson Learning Basic Sampling Issues CHAPTER twelve

2. 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 distinguish between probability samples, and nonprobability samples. 5.To understand sampling implications of surveying over the Internet.

3. Learning Objectives 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. To understand the concept of sampling. The Concept of Sampling

4. Learning Objectives Population or Universe The total group of people from whom we need to obtain information. Define the target market for the product or service in question. Sample versus Census Census: Data about every member of the population. Sample: A subset of the population Definition Of Important Terms To understand the concept of sampling.

5. Learning Objectives Step1. Define the Population of Interest Step 2. Choose Data Collection Method Step 3. Choose Sampling Frame (4) Select a Sampling Method Step 5. Determine Sample Size Step 6. Develop Operational Plan Step 7. Execute Operational Plan Figure 12.1Steps in Developing a Sample Plan

6. Learning Objectives Step One: Defining the Population of Interest Specifying the characteristics from whom information is needed. Define the characteristics of those that should be excluded. Step Two: Choose Data Collection Method Impacts for the sampling process. Step Three: Choosing Sampling Frame A list of elements or members from which we select units to be sampled. To learn the steps in developing a sample plan. Steps In Developing A Sampling Plan

7. Learning Objectives 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 Probability Samples A known, nonzero probability of selection To learn the steps in developing a sample plan. Steps In Developing A Sampling Plan

8. Learning Objectives Nonprobability Samples Elements selected in a nonrandom manner. Advantages of probability samples Obtain information from a representative cross- section Sampling error can be computed The survey results are projectable to the total population. To understand the steps in developing a sample plan. Steps In Developing A Sampling Plan

9. Learning Objectives Disadvantages of probability samples More expansive than nonprobabiity samples of the same size. Probability samples take more time to design and execute. Step Five: Determine Sample Size Available budget Rules of thumb Number of subgroups To distinguish between probability samples and nonprobability samples. Steps In Developing A Sampling Plan

10. Learning Objectives Step Six: Develop of Operational Procedures for Selecting Sample Elements Specify whether a probability or nonprobability sample is being used Step Seven: Execution the Sampling Plan The final step of the operational sampling plan Include adequate checking of specified procedures. To distinguish between probability samples and nonprobability samples. Steps In Developing A Sampling Plan

11. Learning Objectives Sampling methods Probability samples Systemati c Cluster Stratified Simple random Nonprobabilit y samples Convenienc e Judgement Snowball Quota Figure 12.2Classification of Sampling Methods

12. Learning Objectives Sampling Error The error that results when the same sample is not perfectly representative of the population. Two types of sampling error: To understand the concepts of sampling error and nonsampling error. Sampling And Nonsampling Errors  + - ss  ns + - X = X = sample mean  = true population mean ss = sampling error  ns = nonsampling error

13. Learning Objectives Sampling Error The error that results when the same sample is not perfectly representative of the population. Administrative error: problems in the execution of the sample Random error: due to chance and cannot be avoided To understand the concepts of sampling error and nonsampling error. Sampling And Nonsampling Errors

14. Learning Objectives Simple Random Sampling The purest form of probability sample To understand the differences in probability and nonprobability sampling methods. Probability of Selection = Sample Size Population Size Systematic Sampling Uses a fixed skip interval to draw elements from a numbered population. Skip Interval = Population Size Sample Size Probability Sampling Methods

15. Learning Objectives Stratified Samples Probability samples that are distinguished by the following steps: 1. The original population is divided into two or more mutually exclusive and exhaustive subsets 2. Simple random samples of elements from the two or more subsets are chosen independently from each other. To understand the differences in probability and nonprobability sampling methods. Probability Sampling Methods

16. Learning Objectives Three steps involved in implementing a properly stratified sample: 1. Identify salient demographic or classification factors correlated with the behavior of interest. 2. Determine what proportions of the population fall into various sub subgroups under each stratum. proportional allocation disproportional or optimal allocation To understand the differences in probability and nonprobability sampling methods. Probability Sampling Methods

17. Learning Objectives 3. Select separate simple random samples from each stratum. Cluster Samples Sampling units are selected in groups. 1. The population of interest is divided into mutually exclusive and exhaustive subsets. 2. A random sample of the subsets is selected. To understand the differences in probability and nonprobability sampling methods. Probability Sampling Methods

18. Learning Objectives To understand the differences in probability and nonprobability sampling methods. 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. Nonprobability Sampling Methods

19. Learning Objectives 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 Sampling Over the Internet

20. Learning Objectives Don’t Post Surveys in Public Areas Highly biased samples Vested interests quickly To understand sampling implications of surveying over the Internet. Sampling Over the Internet

21. Learning Objectives The Concept of Sampling Definition Of Important Terms Steps In Developing A Sampling Plan Sampling And Nonsampling Errors Probability Sampling Methods Nonprobability Sampling Methods Sampling Over the Internet SUMMARY

22. Learning Objectives The End Copyright © 2002 South-Western/Thomson Learning