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Edition: 97

Copyright: 1997

Publisher: Prentice Hall, Inc.

Published: 1997

International: No

Copyright: 1997

Publisher: Prentice Hall, Inc.

Published: 1997

International: No

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This book's focus is on teaching the statistical procedures for solving applied problems. The authors incorporate a wide range of applications--many from business and economics. Quality and process themes are integrated. Emphasis is placed on the use of statistical programs and the analysis of output. Calculus based material is presented in optional sections.

Provides an early treatment of data collection exploration, experiments, surveys, bivariate data, and scatterplots.

Provides extensive coverage of linear combinations of random variables and correlated random variables in the probability chapters.

Balances coverage with discussions of the teamwork setting that make statistics an exciting and effective problem-solving skill.

Presents quality assurance topics in an extended separate chapter as well as in many applications throughout the book.

Begins each topic with problems posed in applications, followed by a discussion of broad concepts, then by layers of deeper detail.

Integrates Key Idea boxes into each discussion summarizing a specific concept or procedure.

Includes Does It Make Sense? sections to provide practical insights from experienced analysts and to point out judgmental elements of problem solving.

Provides topic selections for a wide range of courses and to extend into students' professional careers as a useful reference.

Discusses each topic on several levels, from broad concepts, to definitions, to assumptions and solved examples.

Offers over 1000 problems including...

Practice problems dispersed throughout discussions to allow immediate feedback on students' understanding of concepts with answers at the end of each chapter.

Short section-ending problems focusing on single ideas and eliciting short responses with answers at the end of the textbook.

Chapter-ending problems that require students to integrate concepts in problem solving with detailed solutions in the Student Solutions Manual.

**1. Introduction. 2. Describing the Data. 3. Descriptive Relationships. 4. Introduction to Probability. 5. Discrete Random Variables and Probability Distribution Functions. 6. Continuous Random Variables and Probability Density Functions. 7. Two Random Variables. 8. Sampling and Data Collection. 9. Distribution of Sample Statistics. 10. Estimation. 11. Hypothesis Testing. 12. Chi Square Tests. 13. Analysis of Variance. 14. Simple Least-Squares Regression. 15. Multiple Regression. 16. Multiple Regression Extensions. 17. Time Series and Forecasting. 18. Quality Assurance. **Appendix A. Probability Tables.

Appendix B. Data Files for Problems and Examples.

Index.

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Summary

This book's focus is on teaching the statistical procedures for solving applied problems. The authors incorporate a wide range of applications--many from business and economics. Quality and process themes are integrated. Emphasis is placed on the use of statistical programs and the analysis of output. Calculus based material is presented in optional sections.

Provides an early treatment of data collection exploration, experiments, surveys, bivariate data, and scatterplots.

Provides extensive coverage of linear combinations of random variables and correlated random variables in the probability chapters.

Balances coverage with discussions of the teamwork setting that make statistics an exciting and effective problem-solving skill.

Presents quality assurance topics in an extended separate chapter as well as in many applications throughout the book.

Begins each topic with problems posed in applications, followed by a discussion of broad concepts, then by layers of deeper detail.

Integrates Key Idea boxes into each discussion summarizing a specific concept or procedure.

Includes Does It Make Sense? sections to provide practical insights from experienced analysts and to point out judgmental elements of problem solving.

Provides topic selections for a wide range of courses and to extend into students' professional careers as a useful reference.

Discusses each topic on several levels, from broad concepts, to definitions, to assumptions and solved examples.

Offers over 1000 problems including...

Practice problems dispersed throughout discussions to allow immediate feedback on students' understanding of concepts with answers at the end of each chapter.

Short section-ending problems focusing on single ideas and eliciting short responses with answers at the end of the textbook.

Chapter-ending problems that require students to integrate concepts in problem solving with detailed solutions in the Student Solutions Manual.

Table of Contents

**1. Introduction. 2. Describing the Data. 3. Descriptive Relationships. 4. Introduction to Probability. 5. Discrete Random Variables and Probability Distribution Functions. 6. Continuous Random Variables and Probability Density Functions. 7. Two Random Variables. 8. Sampling and Data Collection. 9. Distribution of Sample Statistics. 10. Estimation. 11. Hypothesis Testing. 12. Chi Square Tests. 13. Analysis of Variance. 14. Simple Least-Squares Regression. 15. Multiple Regression. 16. Multiple Regression Extensions. 17. Time Series and Forecasting. 18. Quality Assurance. **Appendix A. Probability Tables.

Appendix B. Data Files for Problems and Examples.

Index.

Publisher Info

Publisher: Prentice Hall, Inc.

Published: 1997

International: No

Published: 1997

International: No

This book's focus is on teaching the statistical procedures for solving applied problems. The authors incorporate a wide range of applications--many from business and economics. Quality and process themes are integrated. Emphasis is placed on the use of statistical programs and the analysis of output. Calculus based material is presented in optional sections.

Provides an early treatment of data collection exploration, experiments, surveys, bivariate data, and scatterplots.

Provides extensive coverage of linear combinations of random variables and correlated random variables in the probability chapters.

Balances coverage with discussions of the teamwork setting that make statistics an exciting and effective problem-solving skill.

Presents quality assurance topics in an extended separate chapter as well as in many applications throughout the book.

Begins each topic with problems posed in applications, followed by a discussion of broad concepts, then by layers of deeper detail.

Integrates Key Idea boxes into each discussion summarizing a specific concept or procedure.

Includes Does It Make Sense? sections to provide practical insights from experienced analysts and to point out judgmental elements of problem solving.

Provides topic selections for a wide range of courses and to extend into students' professional careers as a useful reference.

Discusses each topic on several levels, from broad concepts, to definitions, to assumptions and solved examples.

Offers over 1000 problems including...

Practice problems dispersed throughout discussions to allow immediate feedback on students' understanding of concepts with answers at the end of each chapter.

Short section-ending problems focusing on single ideas and eliciting short responses with answers at the end of the textbook.

Chapter-ending problems that require students to integrate concepts in problem solving with detailed solutions in the Student Solutions Manual.

**1. Introduction. 2. Describing the Data. 3. Descriptive Relationships. 4. Introduction to Probability. 5. Discrete Random Variables and Probability Distribution Functions. 6. Continuous Random Variables and Probability Density Functions. 7. Two Random Variables. 8. Sampling and Data Collection. 9. Distribution of Sample Statistics. 10. Estimation. 11. Hypothesis Testing. 12. Chi Square Tests. 13. Analysis of Variance. 14. Simple Least-Squares Regression. 15. Multiple Regression. 16. Multiple Regression Extensions. 17. Time Series and Forecasting. 18. Quality Assurance. **Appendix A. Probability Tables.

Appendix B. Data Files for Problems and Examples.

Index.