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Probability & Statistics for Engineers & Scientists (8E) by Ronald Walpole, Raymond Myers
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About this book :-
Probability & Statistics for Engineers & Scientists (8E) written by Ronald Walpole, Raymond Myers
This book is emphasize a balance between theory and applications. Calculus and other types of mathematical support (e.g., linear algebra) are used at about the same level as in previous editions. The coverage of analytical tools in statistics is enhanced with the use of calculus when discussion centers on rules and concepts in probability. Probability distributions and statistical inference are highlighted in Chapters 2 through 10. Linear algebra and matrices are very lightly applied in Chapters 11 through 15, where linear regression and analysis of variance are covered. Students using this text should have had the equivalent of one semester of differential and integral calculus. Linear algebra is helpful but not necessary so long as the section in Chapter 12 on multiple linear regression using matrix algebra is not covered by the instructor. As in previous editions, a large number of exercises that deal with real-life scientific and engineering applications are available to challenge the student.
Book Detail :-
Title: Probability & Statistics for Engineers & Scientists (8E)
Author(s): Ronald Walpole, Raymond Myers
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About Author :-
The author Ronald Walpole is Ph.D. from Virginia Polytechnic Institute and State University and Professor of statistics, Virginia Tech.
The author Raymond Myers Professor of statistics, Virginia Tech.
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Book Contents :-
Probability & Statistics for Engineers & Scientists (8E) written by
Ronald Walpole, Raymond Myers
cover the following topics.
1. Introduction to Statistics and Data Analysis
3. Random Variables and Probability Distributions
4. Mathematical Expectation
5. Some Discrete Probability Distributions
6. Some Continuous Probability Distributions
7. Functions of Random Variables
8. Fundamental Sampling Distributions and Data Descriptions
9. One- and Two-Sample Estimation Problems
10. One- and Two-Sample Tests of Hypotheses
11. Simple Linear Regression and Correlation
12. Multiple Linear Regression and Certain Nonlinear Regression Models
13. One-Factor Experiments: General
14. Factorial Experiments (Two or More Factors)
15. 2k Factorial Experiments and Fractions
16. Nonparametric Statistics
17. Statistical Quality Control
18. Bayesian Statistics
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