Applied Statistics and Probability for Engineers, 6e
November 2013, ©2014
Applied Statistics and Probability for Engineers, 6th 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, 6e is suitable for either a one- or two-term course in probability and statistics. The 6th edition of this text focuses on real engineering applications and real engineering solutions while including material on the bootstrap, increased emphasis on the use of P-value, coverage of equivalence testing, combining p-values, many new examples and entirely revised homework sections.
Chapter 1 The Role of Statistics in Engineering
Chapter 2 Probability
Chapter 3 Discrete Random Variables and Probability Distributions
Chapter 4 Continuous Random Variables and Probability Distributions
Chapter 5 Joint Probability Distributions
Chapter 6 Descriptive Statistics
Chapter 7 Sampling Distributions and Point Estimation of Parameters
Chapter 8 Statistical Intervals for a Single Sample
Chapter 9 Tests of Hypotheses for a Single Sample
Chapter 10 Statistical Inference for Two Samples
Chapter 11 Simple Linear Regression and Correlation
Chapter 12 Multiple Linear Regression
Chapter 13 Design and Analysis of Single-Factor Experiments: The Analysis of Variance
Chapter 14 Design of Experiments with Several Factors
Chapter 15 Statistical Quality Control
- 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 and almost entirely revised homework exercises sections.
- 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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