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Applied Statistics and Probability for Engineers (3E) by Douglas Montgomery, George Runger
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About this book :-
Applied Statistics and Probability for Engineers (3E) written by Douglas Montgomery, George Runger
This best-selling engineering statistics text provides a practical approach that is more oriented to engineering and the chemical and physical sciences than many similar texts. It's packed with unique problem sets that reflect realistic situations engineers will encounter in their working lives.
Book Detail :-
Title: Applied Statistics and Probability for Engineers
Edition: Third Edition
Author(s): Douglas C. Montgomery and George C. Runger
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About Author :-
The author Douglas C. Montgomery , Arizona State University, Tempe, Arizona, United States. Douglas Montgomery is a Regents Professor of Industrial Engineering and Statistics. His research interests are in industrial statistics. He is an author of 16 books and more than 200 technical papers. He is a recipient of the Shewhart Medal, the Brumbaugh Award, the Hunter Award, and the Shewell Award, and the Ellis R. Ott Award.
The author George C. Runger , Arizona State University, Tempe, Arizona, United States. He researches analytical methods for knowledge generation and data-driven improvements in organizations. He focuses on machine learning for large, complex data, and real-time analysis, with applications to surveillance, decision support, and population health. Previously, he was a senior engineer and technical leader for data analytics projects at IBM. He holds degrees in industrial engineering and statistics. He was the inaugural department editor for healthcare informatics for ISIE Transactions on Healthcare Systems Engineering.
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Book Contents :-
Applied Statistics and Probability for Engineers (3E) written by
Douglas Montgomery, George Runger
cover the following topics.
1 The Role of Statistics in Engineering
3 Discrete Random Variables and Probability Distributions
4 Continuous Random Variables and Probability Distributions
5 Joint Probability Distributions
6 Descriptive Statistics
7 Sampling Distributions and Point Estimation of Parameters
8 Statistical Intervals for a Single Sample
9 Tests of Hypotheses for a Single Sample
10 Statistical Inference for Two Samples
11 Simple Linear Regression and Correlation
12 Multiple Linear Regression
13 Design and Analysis of Single-Factor Experiments: The Analysis of Variance
14 Design of Experiments with Several Factors
15 Statistical Quality Control
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