Applied Statistics And Probability For Engineers 6th Edition Douglas C Montgomery by Douglas C. Montgomery 9781118539712, 9781118744123, 1118539710, 1118744128 instant download after payment.

The text 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, 6th Edition is suitable for either a one- or two-term course in probability and statistics.
New to This Edition
Because computer-intensive methods are so important in the modern use of statistics, material on the bootstrap and its use in constructing confidence intervals has been added
Increased emphasis on the use of P-value in hypothesis testing, throughout the text
Explanations throughout the book have been refined to clarify the concepts, making them easier for students to understand.
The introductory chapter on hypothesis testing now includes coverage of equivalence testing, a technique widely used in the biopharmaceutical industry, but which also has widespread applications in other areas.
Combining P-values when performing multiple tests is included.
Many new examples have been added and the homework exercises have been almost entirely revised.
The Wiley Advantage
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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