Synopses & Reviews
Engineers face numerous uncertainties in the design and development of products and processes. To deal with the uncertainties inherent in measured information, they make use of a variety of statistical techniques. This outstanding text presents single-variable statistical distributions that are useful in engineering design and analysis. It lists significant properties of these distributions and describes methods for estimating parameters and their standard errors, constructing confidence intervals, testing hypotheses, and plotting data. Each distribution is worked through typical applications. Figures are used extensively to clarify concepts. Methods are illustrated by numerous fully worked examples in the form of Mathcad documents that readers can use as templates for their own data, eliminating the need for programming. Intended as both a text and reference, the book assumes an elementary knowledge of calculus and probability. Graduate and advanced undergraduate students, as well as practicing engineers and scientists, will be able to use this book to solve practical problems connected with the uncertainty assessment in a wide range of engineering contexts.
Review
"...the book is well structured and well written, particularly in the stand-alone chapters on the individual distributions...if your work or graduate study involves the statistical analysis of engineering data, Statistical Distributions in Engineering provides a good value reference." Journal of Mechanical Engineering Science
Synopsis
Presents single-variable statistical distributions useful in solving practical problems in a wide range of engineering contexts.
Synopsis
Presents single-variable statistical distributions useful in solving practical problems in a wide range of engineering contexts.
Synopsis
This text deals with some useful ways to model the uncertainty and variation associated with the quantitative information encountered in a wide variety of engineering contexts. All examples are presented as Mathcad documents which can be used as templates, eliminating the need for programming.
Synopsis
This book presents single-variable statistical distributions useful in engineering design and analysis. It lists significant properties of these distributions and describes methods for estimating parameters and their standard errors, constructing confidence intervals, testing hypotheses, and plotting data. Each distribution is worked through typical applications. Methods are illustrated by numerous fully worked examples in the form of Mathcad documents that readers can use as templates for their own data, eliminating the need for programming. Students, engineers and applied scientists will use this book to solve practical problems connected with the uncertainty assessment in a wide range of engineering contexts.
Table of Contents
Preface; Part I. Statistical Background: 1. Introduction; 2. Statistics; 3. Inference; Part II. Discrete Distributions: 4. Introduction to discrete distributions; 5. Hypergeometric distributions; 6. Binomial distributions; 7. Negative binomial distributions; 8. Poisson distributions; Part III. Continuous Distributions: 9. Introduction to continuous distributions; 10. Normal distributions; 11. Log-Normal distributions; 12. Exponential distributions; 13. Gamma distributions; 14. Beta distributions; 15. Gumbel distributions; 16. Frechet distributions; 17. Weibull distributions; Index.