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by Richard L. Scheaffer and James T. McClave

Edition: 4TH 95Copyright: 1995

Publisher: Duxbury Press

Published: 1995

International: No

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This text is designed to teach engineers to think statistically so that data can be collected and used intelligently in solving real problems. Although traditional topics are covered, this edition takes a modern, data-oriented, problem-solving, process-improvement view of engineering statistics. The emphasis is on collecting good data through sample surveys and experiments and on applying the data to real problems.

- An empirical, less formal approach, stressing quality improvement and real data.
- Design of experiments introduced in Chapter 2 and used throughout.
- Early and consistent emphasis on process improvement and on total quality control, with a stress on control charts.
- Graphical content considerably enhanced, especially from a data analysis perspective.
- A rewritten Chapter 1 that establishes a pervasive data analytic tone.
- Most chapters include an
*''Activities for Students''*section, causing students to generate their own data.

1. Data and Decisions.

2. From Data Tables to Disk to Discrete Probability.

3. Discrete Probability Distributions.

4. Continuous Probability Distributions.

5. Multivariate Probability Distributions.

6. Statistics, Sampling Distributions, and Control Charts.

7. Properties of Point Estimates.

8. Hypothesis Testing.

9. Simple Regression.

10. Multiple Regression Analysis.

11. Design of Experiments and the Analysis of Variance.

12. Nonparametric Statistics

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Summary

This text is designed to teach engineers to think statistically so that data can be collected and used intelligently in solving real problems. Although traditional topics are covered, this edition takes a modern, data-oriented, problem-solving, process-improvement view of engineering statistics. The emphasis is on collecting good data through sample surveys and experiments and on applying the data to real problems.

- An empirical, less formal approach, stressing quality improvement and real data.
- Design of experiments introduced in Chapter 2 and used throughout.
- Early and consistent emphasis on process improvement and on total quality control, with a stress on control charts.
- Graphical content considerably enhanced, especially from a data analysis perspective.
- A rewritten Chapter 1 that establishes a pervasive data analytic tone.
- Most chapters include an
*''Activities for Students''*section, causing students to generate their own data.

Table of Contents

1. Data and Decisions.

2. From Data Tables to Disk to Discrete Probability.

3. Discrete Probability Distributions.

4. Continuous Probability Distributions.

5. Multivariate Probability Distributions.

6. Statistics, Sampling Distributions, and Control Charts.

7. Properties of Point Estimates.

8. Hypothesis Testing.

9. Simple Regression.

10. Multiple Regression Analysis.

11. Design of Experiments and the Analysis of Variance.

12. Nonparametric Statistics

Publisher Info

Publisher: Duxbury Press

Published: 1995

International: No

Published: 1995

International: No

This text is designed to teach engineers to think statistically so that data can be collected and used intelligently in solving real problems. Although traditional topics are covered, this edition takes a modern, data-oriented, problem-solving, process-improvement view of engineering statistics. The emphasis is on collecting good data through sample surveys and experiments and on applying the data to real problems.

- An empirical, less formal approach, stressing quality improvement and real data.
- Design of experiments introduced in Chapter 2 and used throughout.
- Early and consistent emphasis on process improvement and on total quality control, with a stress on control charts.
- Graphical content considerably enhanced, especially from a data analysis perspective.
- A rewritten Chapter 1 that establishes a pervasive data analytic tone.
- Most chapters include an
*''Activities for Students''*section, causing students to generate their own data.

1. Data and Decisions.

2. From Data Tables to Disk to Discrete Probability.

3. Discrete Probability Distributions.

4. Continuous Probability Distributions.

5. Multivariate Probability Distributions.

6. Statistics, Sampling Distributions, and Control Charts.

7. Properties of Point Estimates.

8. Hypothesis Testing.

9. Simple Regression.

10. Multiple Regression Analysis.

11. Design of Experiments and the Analysis of Variance.

12. Nonparametric Statistics