Miller & Freund's Probability and Statistics for Engineers (Classic Version)

This title is part of the Pearson Modern Classics series. Pearson Modern Classics are acclaimed titles at a value price. Please visit www.pearsonhighered.com/math-classics-series for a complete list of titles.

For an introductory, one or two semester, or sophomore-junior level course in Probability and Statistics or Applied Statistics for engineering, physical science, and mathematics students.

An Applications-Focused Introduction to Probability and Statistics

Miller & Freund's Probability and Statistics for Engineers is rich in exercises and examples, and explores both elementary probability and basic statistics, with an emphasis on engineering and science applications. Much of the data has been collected from the author's own consulting experience and from discussions with scientists and engineers about the use of statistics in their fields. In later chapters, the text emphasizes designed experiments, especially two-level factorial design. The Ninth Edition includes several new datasets and examples showing application of statistics in scientific investigations, familiarizing students with the latest methods, and readying them to become real-world engineers and scientists.

Richard Johnson is the co-author of seven statistics texts and monographs, including Probability and Statistics for Engineers and Applied Multivariate Statistical Analysis. He was the founding editor of Statistics and Probability Letters and served as editor for 25 years. Besides many years of experience in teaching all levels of statistics courses at the University of Wisconsin, he has published more than 120 technical papers concentrating in the areas of reliability and life testing, multivariate analysis, large sample theory, and applications to engineering. Johnson has presented talks on his research in 23 foreign countries. He is an elected member of the International Statistical Institute, a Fellow of the American Statistical Association, a Fellow of the Institute of Mathematical Statistics, and a Fellow of the Royal Statistical Society.

1. Introduction

2. Organization and Description of Data

3. Probability

4. Probability Distributions

5. Probability Densities

6. Sampling Distributions

7. Inferences Concerning a Mean

8. Comparing Two Treatments

9. Inferences Concerning Variances

10. Inferences Concerning Proportions

11. Regression Analysis

12. Analysis of Variance

13. Factorial Experimentation

14. Nonparametric Tests

15. The Statistical Content of Quality Improvement Programs

16. Application to Reliability and Life Testing

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