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by William Mendenhall and Terry Sincich

Cover type: HardbackEdition: 4TH 95

Copyright: 1995

Publisher: Prentice Hall, Inc.

Published: 1995

International: No

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Illustrates basic statistical concepts with extensive applications in engineering and scientific contexts. The text includes optional theoretical exercises allowing instructors who choose to emphasize theory to do so without requiring additional materials.

- Many new applied exercises are based on information from recent engineering and scientific journals, magazine articles, and news reports; all information is referenced.
- A section on "Detecting Normal Distributions" (Chapter 5) gives students insights on when it is reasonable to assume that underlying data is normally distributed.
- A comprehensive example on model building (Chapter 13).
- Emphasis on the regression approach to a Nova (also presents the traditional approach).
- Two sections discussing principles of experimental design--ie., noise-reducing and volume-increasing design (Chapter 14).
- Section on Total Quality Management (Chapter 16).

1. Introduction.

2. Descriptive Statistics.

3. Probability.

4. Discrete Random Variables.

5. Continuous Random Variables.

6. Bivariate Probability Distributions.

7. Sampling Distributions.

8. Estimation.

9. Tests of Hypothesis.

10. Categorical Data.

11. Simple Linear Regression Analysis.

12. Multiple Regression Analysis.

13. Model Building.

14. Analysis of Variants for designed experiments.

15. Nonparametric Statistics.

16. Statistical Process and Quality Control.

17. Product and System Reliability.

Appendix I. Matrix Algebra.

Appendix II. Useful Statistical Tables.

Appendix III. DDT Analysis on Fish Samples, Tennessee River, Alabama.

Appendix IV. Central Processing Unit(CPU) Times of 1,000 Computer Jobs.

Appendix V. Percentage Iron Content for 390 Iron Ore Specimens.

Appendix VI. ASP Tutorial.

Answers to Selected Exercises.

Index.

Summary

Illustrates basic statistical concepts with extensive applications in engineering and scientific contexts. The text includes optional theoretical exercises allowing instructors who choose to emphasize theory to do so without requiring additional materials.

- Many new applied exercises are based on information from recent engineering and scientific journals, magazine articles, and news reports; all information is referenced.
- A section on "Detecting Normal Distributions" (Chapter 5) gives students insights on when it is reasonable to assume that underlying data is normally distributed.
- A comprehensive example on model building (Chapter 13).
- Emphasis on the regression approach to a Nova (also presents the traditional approach).
- Two sections discussing principles of experimental design--ie., noise-reducing and volume-increasing design (Chapter 14).
- Section on Total Quality Management (Chapter 16).

Table of Contents

1. Introduction.

2. Descriptive Statistics.

3. Probability.

4. Discrete Random Variables.

5. Continuous Random Variables.

6. Bivariate Probability Distributions.

7. Sampling Distributions.

8. Estimation.

9. Tests of Hypothesis.

10. Categorical Data.

11. Simple Linear Regression Analysis.

12. Multiple Regression Analysis.

13. Model Building.

14. Analysis of Variants for designed experiments.

15. Nonparametric Statistics.

16. Statistical Process and Quality Control.

17. Product and System Reliability.

Appendix I. Matrix Algebra.

Appendix II. Useful Statistical Tables.

Appendix III. DDT Analysis on Fish Samples, Tennessee River, Alabama.

Appendix IV. Central Processing Unit(CPU) Times of 1,000 Computer Jobs.

Appendix V. Percentage Iron Content for 390 Iron Ore Specimens.

Appendix VI. ASP Tutorial.

Answers to Selected Exercises.

Index.

Publisher Info

Publisher: Prentice Hall, Inc.

Published: 1995

International: No

Published: 1995

International: No

Illustrates basic statistical concepts with extensive applications in engineering and scientific contexts. The text includes optional theoretical exercises allowing instructors who choose to emphasize theory to do so without requiring additional materials.

- Many new applied exercises are based on information from recent engineering and scientific journals, magazine articles, and news reports; all information is referenced.
- A section on "Detecting Normal Distributions" (Chapter 5) gives students insights on when it is reasonable to assume that underlying data is normally distributed.
- A comprehensive example on model building (Chapter 13).
- Emphasis on the regression approach to a Nova (also presents the traditional approach).
- Two sections discussing principles of experimental design--ie., noise-reducing and volume-increasing design (Chapter 14).
- Section on Total Quality Management (Chapter 16).

2. Descriptive Statistics.

3. Probability.

4. Discrete Random Variables.

5. Continuous Random Variables.

6. Bivariate Probability Distributions.

7. Sampling Distributions.

8. Estimation.

9. Tests of Hypothesis.

10. Categorical Data.

11. Simple Linear Regression Analysis.

12. Multiple Regression Analysis.

13. Model Building.

14. Analysis of Variants for designed experiments.

15. Nonparametric Statistics.

16. Statistical Process and Quality Control.

17. Product and System Reliability.

Appendix I. Matrix Algebra.

Appendix II. Useful Statistical Tables.

Appendix III. DDT Analysis on Fish Samples, Tennessee River, Alabama.

Appendix IV. Central Processing Unit(CPU) Times of 1,000 Computer Jobs.

Appendix V. Percentage Iron Content for 390 Iron Ore Specimens.

Appendix VI. ASP Tutorial.

Answers to Selected Exercises.

Index.