Applied Statistics and Probability for Engineers

7th Australian New Zealand Edition

By: Douglas C. Montgomery, George C. Runger

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Paperback | 9 July 2019 | Edition Number 7

At a Glance

Paperback
864 Pages

Edition Type
Revised

Dimensions(cm)
27.8 x 21.6 x 2.2

Paperback

RRP $164.95

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This book is being used at: University of Queensland

Applied Statistics and Probability for Engineers, 7th Edition provides a practical approach oriented to engineering as well as chemical and physical sciences. Students learn how the material will be relevant in their careers through the integration throughout of unique problem sets that reflect realistic applications and situations. Applied Statistics is suitable for either a one- or two-term course in probability and statistics.

New features to the seventh edition include: a textual focus on real engineering applications and real engineering solutions while including material on the bootstrap, increased emphasis on the use of the P-value, clarification of explanations to make it easier for students to understand concepts, an introductory chapter on hypothesis testing that now includes coverage of equivalence testing, a technique widely used in the biopharmaceutical industry, but which also has widespread applications in other areas, and new examples and revised homework exercises sections.

Book Features:

Real Engineering Applications: Treatment of all topics is oriented towards real engineering applications. In the probability chapters, the authors do not emphasize counting methods or artificial applications such as gambling.
Real Data, Real Engineering Situations: Examples and exercises throughout the text use real data and real engineering situations. This motivates students to learn new concepts and gives them a taste of practical engineering experience.
Probability: Coverage of probability is lively and interesting. It is complete, but carefully presented at an appropriate level of depth for the course.
Regression Modeling, DOE, and SQC: Uniquely thorough amount of coverage of regression modeling, design of engineering experiments, and statistical process control makes the book useful as a reference for many important topics.

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