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by Richard L. Scheaffer, William III Mendenhall and R. Lyman Ott

Cover type: HardbackEdition: 6TH 06

Copyright: 2006

Publisher: Brooks/Cole Publishing Co.

Published: 2006

International: No

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This introductory text on the design and analysis of sample surveys emphasizes the practical aspects of survey problems. It begins with brief chapters on the role of sample surveys in the modern world. Thereafter, each chapter introduces a sample survey design or estimation procedure by describing the pertinent practical problem. The authors describe the methodology proposed for solving the problem and provide the details of the estimation procedure, including a compact presentation of the formulas needed to complete the analysis. Then, a practical example is worked out in complete detail. At the end of each chapter, a wealth of exercises gives students ample opportunity to practice the techniques and stretch their grasp of ideas.

Benefits:

- NEW! This edition bridges the gap between classroom and practice in the area of sample survey design and analysis. This begins with the discussion of weights in Chapter 3 and continues through the new sections on weights in unequal probability sampling and adjustments for nonresponse in Chapter 11, which now includes the use of imputation as a technique for handling some types of nonresponse.
- NEW! A modern technique for establishing margins of error and confidence intervals in complex designs, the bootstrap, is introduced, as is an adaptive sampling technique for improving estimates while the field work is in progress.
- NEW! Data sets have been updated and new exercises appear throughout.
- NEW! An effort was made to make the computations compatible with modern statistical software; hand calculation formulas have been de-emphasized.
- NEW! Simulations to demonstrate key statistical concepts have been added, along with suggestions on how the student might expand on these.
- Practical aspects of conducting sample surveys are emphasized, with sections on sources of errors in surveys, methods of data collection, designing questionnaires, and guidelines for planning surveys.
- The "Experiences with Real Data" sections at the end of most chapters include suggestions on how the student can become involved with real sampling problems. By working with large and small projects, some requiring computations to be handled by a computer, students learn to think about every aspect of the survey and realize that some ideas that sound simple in the textbook are not so easily carried out in practice.
- Examples and exercises have been selected from many fields of application.

1. INTRODUCTION.

2. ELEMENTS OF THE SAMPLING PROBLEM.

Introduction. Technical Terms. How to Select the Sample: The Design of the Sample Survey. Sources of Errors in Surveys. Designing a Questionnaire. Planning a Survey. Summary.

3. SOME BASIC CONCEPTS OF STATISTICS.

Introduction. Summarizing Information in Populations and Samples: The Infinite Population Case. Summarizing Information in Populations and Samples: The Finite Population Case. Sampling Distributions. Covariance and Correlation. Estimation. Summary.

4. SIMPLE RANDOM SAMPLING.

Introduction. How to Draw a Simple Random Sample. Estimation of a Population Mean and Total. Selecting the Sample Size for Estimating Population Means and Totals. Estimation of a Population Proportion. Comparing Estimates. Summary.

5. STRATIFIED RANDOM SAMPLING.

Introduction. How to Draw a Stratified Random Sample. Estimation of a Population Mean and Total. Selecting the Sample Size for Estimating Population Means and Totals. Allocation of the Sample. Estimation of a Population Proportion. Selecting the Sample Size and Allocating the Sample to Estimate Proportions. Additional Comments on Stratified Sampling. An Optimal Rule for Choosing Strata. Stratification after Selection of the Sample. Double Sampling for Stratification. Summary.

6. RATIO, REGRESSION, AND DIFFERENCE ESTIMATION.

Introduction. Surveys that Require the Use of Ratio Estimators. Ratio Estimation Using Simple Random Sampling. Selecting the Sample Size. Ratio Estimation in Stratified Random Sampling. Regression Estimation. Difference Estimation. Relative Efficiency of Estimators. Summary.

7. SYSTEMATIC SAMPLING.

Introduction. How to Draw a Systematic Sample. Estimation of a Population Mean and Total. Estimation of a Population Proportion. Selecting the Sample Size. Repeated Systematic Sampling. Further Discussion of Variance Estimators. Summary.

8. CLUSTER SAMPLING.

Introduction. How to Draw a Cluster Sample. Estimation of a Population Mean and Total. Equal Cluster Sizes; Comparison to Simple Random Sampling. Selecting the Sample Size for Estimating Population Means and Totals. Estimation of a Population Proportion. Selecting the Sample Size for Estimating Proportions. Cluster Sampling Combined with Stratification. Cluster Sampling with Probabilities Proportional to Size. Summary.

9. TWO-STAGE CLUSTER SAMPLING.

Introduction. How to Draw a Two-Stage Cluster Sample. Unbiased Estimation of a Population Mean and Total. Ratio Estimation of a Population Mean. Estimation of a Population Proportion. Sampling Equal-Sized Clusters. Two-Stage Cluster Sampling with Probabilities Proportional to Size. Summary.

10. ESTIMATING THE POPULATION SIZE.

Introduction. Estimation of a Population Size Using Direct Sampling. Estimation of a Population Size Using Inverse Sampling. Choosing Sample Sizes for Direct and Inverse Sampling. Estimating Population Density and Size from Quadrat Samples. Estimating Population Density and Size from Stocked Quadrats. Adaptive Sampling. Summary.

11. SUPPLEMENTAL TOPICS.

Introduction. Interpenetrating Subsamples. Estimation of Means and Totals over Subpopulations. Random-Response Model.

Use of Weights in Sample Surveys. Adjusting for Nonresponse. Imputation. Selecting the Number of Callbacks. The Bootstrap. Summary.

12. SUMMARY.

Summary of the Designs and Methods. Comparisons among the Designs and Methods.

Appenidices.

References and Bibliography Tables. Derivation of Some Main Results. Macros for MINITAB. Macros for SAS. Data Sets.

Selected Answers.

Index.

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Summary

This introductory text on the design and analysis of sample surveys emphasizes the practical aspects of survey problems. It begins with brief chapters on the role of sample surveys in the modern world. Thereafter, each chapter introduces a sample survey design or estimation procedure by describing the pertinent practical problem. The authors describe the methodology proposed for solving the problem and provide the details of the estimation procedure, including a compact presentation of the formulas needed to complete the analysis. Then, a practical example is worked out in complete detail. At the end of each chapter, a wealth of exercises gives students ample opportunity to practice the techniques and stretch their grasp of ideas.

Benefits:

- NEW! This edition bridges the gap between classroom and practice in the area of sample survey design and analysis. This begins with the discussion of weights in Chapter 3 and continues through the new sections on weights in unequal probability sampling and adjustments for nonresponse in Chapter 11, which now includes the use of imputation as a technique for handling some types of nonresponse.
- NEW! A modern technique for establishing margins of error and confidence intervals in complex designs, the bootstrap, is introduced, as is an adaptive sampling technique for improving estimates while the field work is in progress.
- NEW! Data sets have been updated and new exercises appear throughout.
- NEW! An effort was made to make the computations compatible with modern statistical software; hand calculation formulas have been de-emphasized.
- NEW! Simulations to demonstrate key statistical concepts have been added, along with suggestions on how the student might expand on these.
- Practical aspects of conducting sample surveys are emphasized, with sections on sources of errors in surveys, methods of data collection, designing questionnaires, and guidelines for planning surveys.
- The "Experiences with Real Data" sections at the end of most chapters include suggestions on how the student can become involved with real sampling problems. By working with large and small projects, some requiring computations to be handled by a computer, students learn to think about every aspect of the survey and realize that some ideas that sound simple in the textbook are not so easily carried out in practice.
- Examples and exercises have been selected from many fields of application.

Table of Contents

1. INTRODUCTION.

2. ELEMENTS OF THE SAMPLING PROBLEM.

Introduction. Technical Terms. How to Select the Sample: The Design of the Sample Survey. Sources of Errors in Surveys. Designing a Questionnaire. Planning a Survey. Summary.

3. SOME BASIC CONCEPTS OF STATISTICS.

Introduction. Summarizing Information in Populations and Samples: The Infinite Population Case. Summarizing Information in Populations and Samples: The Finite Population Case. Sampling Distributions. Covariance and Correlation. Estimation. Summary.

4. SIMPLE RANDOM SAMPLING.

Introduction. How to Draw a Simple Random Sample. Estimation of a Population Mean and Total. Selecting the Sample Size for Estimating Population Means and Totals. Estimation of a Population Proportion. Comparing Estimates. Summary.

5. STRATIFIED RANDOM SAMPLING.

Introduction. How to Draw a Stratified Random Sample. Estimation of a Population Mean and Total. Selecting the Sample Size for Estimating Population Means and Totals. Allocation of the Sample. Estimation of a Population Proportion. Selecting the Sample Size and Allocating the Sample to Estimate Proportions. Additional Comments on Stratified Sampling. An Optimal Rule for Choosing Strata. Stratification after Selection of the Sample. Double Sampling for Stratification. Summary.

6. RATIO, REGRESSION, AND DIFFERENCE ESTIMATION.

Introduction. Surveys that Require the Use of Ratio Estimators. Ratio Estimation Using Simple Random Sampling. Selecting the Sample Size. Ratio Estimation in Stratified Random Sampling. Regression Estimation. Difference Estimation. Relative Efficiency of Estimators. Summary.

7. SYSTEMATIC SAMPLING.

Introduction. How to Draw a Systematic Sample. Estimation of a Population Mean and Total. Estimation of a Population Proportion. Selecting the Sample Size. Repeated Systematic Sampling. Further Discussion of Variance Estimators. Summary.

8. CLUSTER SAMPLING.

Introduction. How to Draw a Cluster Sample. Estimation of a Population Mean and Total. Equal Cluster Sizes; Comparison to Simple Random Sampling. Selecting the Sample Size for Estimating Population Means and Totals. Estimation of a Population Proportion. Selecting the Sample Size for Estimating Proportions. Cluster Sampling Combined with Stratification. Cluster Sampling with Probabilities Proportional to Size. Summary.

9. TWO-STAGE CLUSTER SAMPLING.

Introduction. How to Draw a Two-Stage Cluster Sample. Unbiased Estimation of a Population Mean and Total. Ratio Estimation of a Population Mean. Estimation of a Population Proportion. Sampling Equal-Sized Clusters. Two-Stage Cluster Sampling with Probabilities Proportional to Size. Summary.

10. ESTIMATING THE POPULATION SIZE.

Introduction. Estimation of a Population Size Using Direct Sampling. Estimation of a Population Size Using Inverse Sampling. Choosing Sample Sizes for Direct and Inverse Sampling. Estimating Population Density and Size from Quadrat Samples. Estimating Population Density and Size from Stocked Quadrats. Adaptive Sampling. Summary.

11. SUPPLEMENTAL TOPICS.

Introduction. Interpenetrating Subsamples. Estimation of Means and Totals over Subpopulations. Random-Response Model.

Use of Weights in Sample Surveys. Adjusting for Nonresponse. Imputation. Selecting the Number of Callbacks. The Bootstrap. Summary.

12. SUMMARY.

Summary of the Designs and Methods. Comparisons among the Designs and Methods.

Appenidices.

References and Bibliography Tables. Derivation of Some Main Results. Macros for MINITAB. Macros for SAS. Data Sets.

Selected Answers.

Index.

Publisher Info

Publisher: Brooks/Cole Publishing Co.

Published: 2006

International: No

Published: 2006

International: No

This introductory text on the design and analysis of sample surveys emphasizes the practical aspects of survey problems. It begins with brief chapters on the role of sample surveys in the modern world. Thereafter, each chapter introduces a sample survey design or estimation procedure by describing the pertinent practical problem. The authors describe the methodology proposed for solving the problem and provide the details of the estimation procedure, including a compact presentation of the formulas needed to complete the analysis. Then, a practical example is worked out in complete detail. At the end of each chapter, a wealth of exercises gives students ample opportunity to practice the techniques and stretch their grasp of ideas.

Benefits:

- NEW! This edition bridges the gap between classroom and practice in the area of sample survey design and analysis. This begins with the discussion of weights in Chapter 3 and continues through the new sections on weights in unequal probability sampling and adjustments for nonresponse in Chapter 11, which now includes the use of imputation as a technique for handling some types of nonresponse.
- NEW! A modern technique for establishing margins of error and confidence intervals in complex designs, the bootstrap, is introduced, as is an adaptive sampling technique for improving estimates while the field work is in progress.
- NEW! Data sets have been updated and new exercises appear throughout.
- NEW! An effort was made to make the computations compatible with modern statistical software; hand calculation formulas have been de-emphasized.
- NEW! Simulations to demonstrate key statistical concepts have been added, along with suggestions on how the student might expand on these.
- Practical aspects of conducting sample surveys are emphasized, with sections on sources of errors in surveys, methods of data collection, designing questionnaires, and guidelines for planning surveys.
- The "Experiences with Real Data" sections at the end of most chapters include suggestions on how the student can become involved with real sampling problems. By working with large and small projects, some requiring computations to be handled by a computer, students learn to think about every aspect of the survey and realize that some ideas that sound simple in the textbook are not so easily carried out in practice.
- Examples and exercises have been selected from many fields of application.

2. ELEMENTS OF THE SAMPLING PROBLEM.

Introduction. Technical Terms. How to Select the Sample: The Design of the Sample Survey. Sources of Errors in Surveys. Designing a Questionnaire. Planning a Survey. Summary.

3. SOME BASIC CONCEPTS OF STATISTICS.

Introduction. Summarizing Information in Populations and Samples: The Infinite Population Case. Summarizing Information in Populations and Samples: The Finite Population Case. Sampling Distributions. Covariance and Correlation. Estimation. Summary.

4. SIMPLE RANDOM SAMPLING.

Introduction. How to Draw a Simple Random Sample. Estimation of a Population Mean and Total. Selecting the Sample Size for Estimating Population Means and Totals. Estimation of a Population Proportion. Comparing Estimates. Summary.

5. STRATIFIED RANDOM SAMPLING.

Introduction. How to Draw a Stratified Random Sample. Estimation of a Population Mean and Total. Selecting the Sample Size for Estimating Population Means and Totals. Allocation of the Sample. Estimation of a Population Proportion. Selecting the Sample Size and Allocating the Sample to Estimate Proportions. Additional Comments on Stratified Sampling. An Optimal Rule for Choosing Strata. Stratification after Selection of the Sample. Double Sampling for Stratification. Summary.

6. RATIO, REGRESSION, AND DIFFERENCE ESTIMATION.

Introduction. Surveys that Require the Use of Ratio Estimators. Ratio Estimation Using Simple Random Sampling. Selecting the Sample Size. Ratio Estimation in Stratified Random Sampling. Regression Estimation. Difference Estimation. Relative Efficiency of Estimators. Summary.

7. SYSTEMATIC SAMPLING.

Introduction. How to Draw a Systematic Sample. Estimation of a Population Mean and Total. Estimation of a Population Proportion. Selecting the Sample Size. Repeated Systematic Sampling. Further Discussion of Variance Estimators. Summary.

8. CLUSTER SAMPLING.

Introduction. How to Draw a Cluster Sample. Estimation of a Population Mean and Total. Equal Cluster Sizes; Comparison to Simple Random Sampling. Selecting the Sample Size for Estimating Population Means and Totals. Estimation of a Population Proportion. Selecting the Sample Size for Estimating Proportions. Cluster Sampling Combined with Stratification. Cluster Sampling with Probabilities Proportional to Size. Summary.

9. TWO-STAGE CLUSTER SAMPLING.

Introduction. How to Draw a Two-Stage Cluster Sample. Unbiased Estimation of a Population Mean and Total. Ratio Estimation of a Population Mean. Estimation of a Population Proportion. Sampling Equal-Sized Clusters. Two-Stage Cluster Sampling with Probabilities Proportional to Size. Summary.

10. ESTIMATING THE POPULATION SIZE.

Introduction. Estimation of a Population Size Using Direct Sampling. Estimation of a Population Size Using Inverse Sampling. Choosing Sample Sizes for Direct and Inverse Sampling. Estimating Population Density and Size from Quadrat Samples. Estimating Population Density and Size from Stocked Quadrats. Adaptive Sampling. Summary.

11. SUPPLEMENTAL TOPICS.

Introduction. Interpenetrating Subsamples. Estimation of Means and Totals over Subpopulations. Random-Response Model.

Use of Weights in Sample Surveys. Adjusting for Nonresponse. Imputation. Selecting the Number of Callbacks. The Bootstrap. Summary.

12. SUMMARY.

Summary of the Designs and Methods. Comparisons among the Designs and Methods.

Appenidices.

References and Bibliography Tables. Derivation of Some Main Results. Macros for MINITAB. Macros for SAS. Data Sets.

Selected Answers.

Index.