©The McGraw-Hill Companies, Inc., 2001Irwin/McGraw-Hill Donald Cooper Pamela Schindler Chapter 7 Business Research Methods.

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©The McGraw-Hill Companies, Inc., 2001Irwin/McGraw-Hill Donald Cooper Pamela Schindler Chapter 7 Business Research Methods

©The McGraw-Hill Companies, Inc., 2001Irwin/McGraw-Hill Chapter 7 Sampling Design

 The McGraw-Hill Companies, Inc., 2001 Irwin/McGraw-Hill Click to edit Master title style Selection of Elements Population Population Element Sampling Census Slide 7 - 1

 The McGraw-Hill Companies, Inc., 2001 Irwin/McGraw-Hill Click to edit Master title style What is a Good Sample? äAccurate: absence of bias äPrecise estimate: sampling error Slide 7 - 2

 The McGraw-Hill Companies, Inc., 2001 Irwin/McGraw-Hill Click to edit Master title style Types of Sampling Designs Probability Nonprobability Slide 7 - 3

 The McGraw-Hill Companies, Inc., 2001 Irwin/McGraw-Hill Click to edit Master title style Steps in Sampling Design äWhat is the relevant population? äWhat are the parameters of interest? What is the sampling frame? äWhat is the type of sample? äWhat size sample is needed? äHow much will it cost? Slide 7 - 4

 The McGraw-Hill Companies, Inc., 2001 Irwin/McGraw-Hill Click to edit Master title style Concepts to help understand Probability Sampling Standard error Confidence interval Central limit theorem Slide 7 - 5

 The McGraw-Hill Companies, Inc., 2001 Irwin/McGraw-Hill Click to edit Master title style Probability Sampling Designs Simple random Systematic Stratified äProportionate äDisproportionate Cluster Double Slide 7 - 6

 The McGraw-Hill Companies, Inc., 2001 Irwin/McGraw-Hill Click to edit Master title style Designing Cluster Samples äHow homogeneous are the clusters? äShall we seek equal or unequal clusters? äHow large a cluster shall we take? äShall we use a single-stage or multistage cluster? äHow large a sample is needed? Slide 7 - 7

 The McGraw-Hill Companies, Inc., 2001 Irwin/McGraw-Hill Click to edit Master title style Slide Nonprobability Sampling Reasons to use äProcedure satisfactorily meets the sampling objectives äLower Cost äLimited Time äNot as much human error as selecting a completely random sample äTotal list population not available

 The McGraw-Hill Companies, Inc., 2001 Irwin/McGraw-Hill Click to edit Master title style Nonprobability Sampling Convenience Sampling Purposive Sampling äJudgment Sampling äQuota Sampling Snowball Sampling Slide 7 - 9