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Ross S.M. Introduction to Probability and Statistics for Engineers and Scientists

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Ross S.M. Introduction to Probability and Statistics for Engineers and Scientists
Elsevier Science, 2014. — 730 p. — 5th ed. — ISBN: 0123948118, 9780123948113
Introduction to Probability and Statistics for Engineers and Scientists provides a superior introduction to applied probability and statistics for engineering or science majors. Ross emphasizes the manner in which probability yields insight into statistical problems ultimately resulting in an intuitive understanding of the statistical procedures most often used by practicing engineers and scientists. Real data sets are incorporated in a wide variety of exercises and examples throughout the book, and this emphasis on data motivates the probability coverage. As with the previous editions, Ross' text has tremendously clear exposition, plus real-data examples and exercises throughout the text. Numerous exercises, examples, and applications connect probability theory to everyday statistical problems and situations.
Clear exposition by a renowned expert author
Real data examples that use significant real data from actual studies across life science, engineering, computing and business
End of Chapter review material that emphasizes key ideas as well as the risks associated with practical application of the material*25% New Updated problem sets and applications, that demonstrate updated applications to engineering as well as biological, physical and computer science
New additions to proofs in the estimation section
New coverage of Pareto and lognormal distributions, prediction intervals, use of dummy variables in multiple regression models, and testing equality of multiple population distributions.
Contents:
Preface.
ntroduction to Statistics.
Descriptive Statistics.
Elements of Probability.
Random Variables and Expectation.
Special Random Variables.
Distributions of Sampling Statistics.
Parameter Estimation.
Hypothesis Testing.
Regression.
Analysis of Variance.
Goodness of Fit Tests and Categorical Data Analysis.
non parametric HypothesisTests.
Quality Control.
LifeTesting.
Simulation, Bootstrap Statistical Methods, and Permutation Tests.
Appendix of Tables.
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