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Applied Statistics and Probability for Engineers, Student Solutions Manual, 5th Edition

John Wiley and Sons Ltd, Sep 2010, Pages: 392


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Montgomery and Runger's bestselling engineering statistics text provides a practical approach oriented to engineering as well as chemical and physical sciences. By providing unique problem sets that reflect realistic situations, students learn how the material will be relevant in their careers. With a focus on how statistical tools are integrated into the engineering problem-solving process, all major aspects of engineering statistics are covered. Developed with sponsorship from the National Science Foundation, this text incorporates many insights from the authors' teaching experience along with feedback from numerous adopters of previous editions.

New Features to this Edition:

- Nonparametric Statistics is now integrated into mainstream hypothesis testing in Chapters 9 and 10, rather than in a separate chapter (formerly Chapter 15 in the Fourth Edition).

- p-value: increased emphasis on p-value in hypothesis testing,

- Beta distribution has been added

- Practical interpretations: brief comments have been added at the end of many examples to emphasise the practical interpretations of the results.

- New homework problems: 200 new homework problems have been added

Hallmark Features:

Real Engineering Applications:

- Treatment of all topics is oriented towards real engineering applications. In the probability chapters, the authors do not emphasise counting methods or artificial applications such as gambling.

Real Data, Real Engineering Situations:

Examples and exercises throughout 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 concise so as not to take over the content of the entire text.

Regression Modeling, DOE, and SQC:

- An unusually 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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