This leads to a clear and more readable writing style that students understand and appreciate. Additionally, because of his intimacy with the professional community, Hayter includes many high-interest examples and datasets that keep students’ attention throughout the term. PROBABILITY AND STATISTICS FOR ENGINEERS AND SCIENTISTS employs a flexible approach with regard to the use of computer tools. Because the book is not tied to a particular software package, instructors may choose the program that best suits their needs.
Through the use of extensive examples and datasets, the book illustrates the importance of statistical data collection and analysis for students in the fields of aerospace, biochemical, civil, electrical, environmental, industrial, mechanical, and textile engineering, as well as for students in physics, chemistry, computing, biology, management, and mathematics.
2. Random variables.
3. Discrete probability distributions.
4. Continuous probability distributions.
5. The normal distribution.
6. Descriptive statistics.
7. Statistical estimation and sampling distributions.
8. Inferences on a population mean.
9. Comparing two population means.
10. Discrete data analysis.
11. The analysis of variance.
12. Simple linear regression and correlation.
13. Multiple linear regression and nonlinear regression.
14. Multifactor experimental design and analysis.
15. Nonparametric statistical analysis.
16. Quality control methods.
17. Reliability analysis and life testing.
Answers to odd-numbered problems.
Anthony J. Hayter
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