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. 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. 뷧eal 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. 뷥robability: Coverage of probability is lively and interesting. It is complete, but carefully presented at an appropriate level of depth for the course 뷧egression 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. 뷭ileyPLUS is a research-based online environment for effective teaching and learning. WileyPLUS is packed with interactive study tools and resources뻟ncluding the complete online textbook뻯o give your students more value for their money.

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

Appendices

DDouglas C. Montgomery, Regents' Professor of Industrial Engineering and Statistics at Arizona State University, received his B.S., M.S., and Ph.D. degrees from Virginia Polytechnic Institute, all in engineering. From 1969 to 1984, he was a faculty member of the School of Industrial & Systems Engineering at the Georgia Institute of Technology; from 1984 to 1988, he was at the University of Washington, where he held the John M. Fluke Distinguished chair of Manufacturing Engineering, was Professor of Mechanical Engineering, and Director of the Program in industrial Engineering. He has authored and coauthored many technical papers as well as twelve other books. Dr. Montgomery is a Stewart Medalist of the American Society for Quality, and has also received the Brumbaugh Award, the William G. Hunter Award, and the Shewell Award (twice) from the ASQ.

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