Statistics in Engineering

With Examples in MATLAB® and R, Second Edition

Andrew Smith author David Green author Andrew Metcalfe author Tony Greenfield author Jonathan Tuke author Mayhayaudin Mansor author

Format:Hardback

Publisher:Taylor & Francis Inc

Published:29th Jan '19

£86.99

Available to order, but very limited on stock - if we have issues obtaining a copy, we will let you know.

This hardback is available in another edition too:

Statistics in Engineering cover

Engineers are expected to design structures and machines that can operate in challenging and volatile environments, while allowing for variation in materials and noise in measurements and signals. Statistics in Engineering, Second Edition: With Examples in MATLAB and R covers the fundamentals of probability and statistics and explains how to use these basic techniques to estimate and model random variation in the context of engineering analysis and design in all types of environments.

The first eight chapters cover probability and probability distributions, graphical displays of data and descriptive statistics, combinations of random variables and propagation of error, statistical inference, bivariate distributions and correlation, linear regression on a single predictor variable, and the measurement error model. This leads to chapters including multiple regression; comparisons of several means and split-plot designs together with analysis of variance; probability models; and sampling strategies. Distinctive features include:

  • All examples based on work in industry, consulting to industry, and research for industry
  • Examples and case studies include all engineering disciplines
  • Emphasis on probabilistic modeling including decision trees, Markov chains and processes, and structure functions
  • Intuitive explanations are followed by succinct mathematical justifications
  • Emphasis on random number generation that is used for stochastic simulations of engineering systems, demonstration of key concepts, and implementation of bootstrap methods for inference
  • Use of MATLAB and the open source software R, both of which have an extensive range of statistical functions for standard analyses and also enable programing of specific applications
  • Use of multiple regression for times series models and analysis of factorial and central composite designs
  • Inclusion of topics such as Weibull analysis of failure times and split-plot designs that are commonly used in industry but are not usually included in introductory textbooks
  • Experiments designed to show fundamental concepts that have been tested with large classes working in small groups
  • Website with additional materials that is regularly updated

Andrew Metcalfe, David Green, Andrew Smith, and Jonathan Tuke have taught probability and statistics to students of engineering at the University of Adelaide for many years and have substantial industry experience. Their current research includes applications to water resources engineering, mining, and telecommunications. Mahayaudin Mansor worked in banking and insurance before teaching statistics and business mathematics...

"Statistics in Engineering: With Examples in MATLAB and R" is an ideal and unreservedly recommended textbook for college and university library collections."
~John Burroughs, Reviewer's Bookwatch

"Distinctive features of this new second edition of Statistics in Engineering iinclude: All examples being based on work in industry, consulting to industry, and research for industry; Emphasis on probabilistic modeling including decision trees, Markov chains and processes, and structure functions; Intuitive explanations are followed by succinct mathematical justifications; Emphasis on random number generation that is used for stochastic simulations of engineering systems, demonstration of key concepts, and implementation of bootstrap methods for inference; Use of MATLAB and the open source software R, both of which have an extensive range of statistical functions for standard analyses and also an extensive range of statistical functions for standard analyses and also enable programming of specific applications; Use of multiple regression for times series models and analysis of factorial and central composite for time series models and analysis of factorial and central composite designs; Inclusion of topics such as Weibull analysis of failure times and split-plot designs that are commonly used in industry but are not usually included in introductory textbooks: Experiments designed to show fundamental concepts that have been tested with large classes working in small groups."
~Midwest Book Review

ISBN: 9781439895474

Dimensions: unknown

Weight: 1515g

810 pages

2nd edition