Engineering Statistics, Textbook and Student Study

by ; ;
Edition: 3rd
Format: Hardcover
Pub. Date: 2005-07-31
Publisher(s): John Wiley & Sons Inc
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Summary

The same statistical tools that professional engineers depend on With a strong emphasis on the statistical techniques most often used in engineering practice, Montgomery Runger, and Hubele's ENGINEERING STATISTICS, presents all the key material that engineers need to know in a concise framework. All major aspects of engineering statistics are covered including descriptive statistics, probability and probability distributions, statistical tests and confidence intervals for one and two samples, building regression models, designing and analyzing engineering experiments, and Statistical process control. Revised and enhanced, the Third Edition presents an even better integration of probability and statistics into the overall engineering problem-solving process, including discussion and illustration of retrospective studies, observational studies, and designed experiments. Highlights of the Third Edition Presents expanded coverage of functions of random variables, transmission of error, and measurement systems capability analysis-important topics for all engineers. Coverage of data display and analysis features expanded use of graphics, including multivariate plots. Thoroughly revised coverage of regression, with an increased emphasis on Minitab, eliminates the need for matrix algebra. All examples and exercises, including many new to this edition, are based on real-world applications of statistics in engineering. Many feature real data from published sources. Provides unusually thorough, yet concise, coverage of regression modeling, design of engineering experiments, and statistical process control. Minitab is well integrated into the text and used for many example solutions. All data sets are available in electronic form.

Table of Contents

1.     The Role of Statistics in Engineering
2.     Data Summary and Presentation
3.     Random Variables and Probability Distributions
4.     Decision Making for a Single Sample
5.     Decision Making for Two Samples
6.     Building Empirical Models
7.     Design of Engineering Experiments
8.Statistical Quality Control
Appendices
Index

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