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Statistics in Engineering - With Examples in MATLAB (R) and R, Second Edition (Hardcover, 2nd edition)
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Statistics in Engineering - With Examples in MATLAB (R) and R, Second Edition (Hardcover, 2nd edition)
Series: Chapman & Hall/CRC Texts in Statistical Science
Expected to ship within 12 - 19 working days
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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 at
the Universiti Tun Abdul Razak Malaysia and is currently a
researcher specializing in data analytics and quantitative research
in the Health Economics and Social Policy Research Group at the
Australian Centre for Precision Health, University of South
Australia. Tony Greenfield, formerly Head of Process Computing and
Statistics at the British Iron and Steel Research Association, is a
statistical consultant. He has been awarded the Chambers Medal for
outstanding services to the Royal Statistical Society; the George
Box Medal by the European Network for Business and Industrial
Statistics for Outstanding Contributions to Industrial Statistics;
and the William G. Hunter Award by the American Society for
Quality.
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