Engineering Statistics Demystified / Edition 1

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Learn how to implement statistics in engineering applications — even if you don't have formal training, unlimited time, or a genius IQ. Engineering Statistics Demystified offers an effective, enlightening, and entertaining way to learn this complex subject.

Written by statistics professor Larry J. Stephens, this book introduces you to several statistical software programs and encourages you to use these programs along with the book. You'll study probability distributions for discrete and continuous random variables as well as sampling distributions, and make statistical inferences concerning means, variances, and proportions. Packed with examples from the featured statistical programs and including end-of-chapter exercises and two final exams, this book will teach you the fundamentals of engineering statistics in no time at all.

This hands-on, self-teaching guide offers:

  • An easy way to understand engineering statistics
  • Explanations on how to use several statistical software programs, including EXCEL, MINITAB, SAS, SPSS, STATISTIX, and MAPLE
  • Real-world examples
  • Exercises at the end of each chapter to reinforce learning and pinpoint weaknesses
  • Two final exams at the end of the book, along with their solutions
  • A time-saving approach to performing better on an exam or at work

Simple enough for a beginner, but challenging enough for an advanced student, Engineering Statistics Demystified is your shortcut to mastering this challenging topic.

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Product Details

  • ISBN-13: 9780071462723
  • Publisher: McGraw-Hill Professional Publishing
  • Publication date: 12/13/2006
  • Series: Demystified Series
  • Edition number: 1
  • Pages: 448
  • Sales rank: 869,935
  • Product dimensions: 7.30 (w) x 9.20 (h) x 1.02 (d)

Meet the Author

Larry Stephens is a professor of mathematics

at the University of Nebraska and has also worked for NASA. He

is the author of McGraw-Hill's Advanced Statistics Demystified and

Schaum's Outline of Beginning Statistics.

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Table of Contents

Preface     xi
Acknowledgments     xiii
Treatment of Data Using EXCEL, MINITAB, SAS, SPSS, and STATISTIX     1
Graphical Displays of Data     1
Descriptive Measures of Data     13
Measures of Relative Standing     18
Exercises     23
Summary     29
Probability     33
Sample Space, Events, and Operations on Events     33
The Multiplicative Rule, Permutations, and Combinations     38
Probability     41
The Axioms of Probability     42
Some Elementary Theorems (Rules) of Probability     44
Conditional Probability     48
Bayes' Theorem     52
Mathematical Expectation     53
Exercises     56
Summary     59
Probability Distributions for Discrete Random Variables     61
Random Variables     61
The Mean and Standard Deviation of a Probability Distribution     71
Chebyshev's Theorem     75
The Binomial Distribution     77
The Hypergeometric Distribution     84
The Geometric Distribution     88
The Negative Binomial Distribution     91
The PoissonDistribution     94
The Multinomial Distribution     97
Simulation     99
Exercises     104
Summary     108
Probability Densities for Continuous Random Variables and Introduction to MAPLE     113
Continuous Random Variables     113
The Normal Distribution     123
The Normal Approximation to the Binomial Distribution     128
The Uniform Distribution     133
The Log-Normal Distribution     134
The Gamma Distribution     138
The Beta Distribution     143
The Weibull Distribution     146
Joint Distributions-Discrete and Continuous     151
Checking Data for Normality     154
Transforming Observations to Near Normality     158
Simulation     160
Exercises     164
Summary     168
Sampling Distributions     173
Populations and Samples     173
The Sampling Distribution of the Mean ([sigma] Known)     174
The Sampling Distribution of the Mean ([sigma] Unknown)     183
The Sampling Distribution of the Proportion     191
The Sampling Distribution of the Variance     193
Exercises      197
Summary     200
Inferences Concerning Means     203
Point Estimation     203
Interval Estimation     208
Basic Concepts of Testing Hypotheses     217
Testing Hypothesis About a Single Mean     223
The Relationship between Tests of Hypothesis and Confidence Intervals     228
Inferences Concerning Two Means-Independent and Large Samples     230
Inferences Concerning Two Means-Independent and Small Samples     233
Inferences Concerning Two Means-Dependent Samples     245
Exercises     248
Summary     252
Inferences Concerning Variances     259
The Estimation of Variances     259
Hypotheses Concerning One Variance     265
Hypotheses Concerning Two Variances     272
Exercises     278
Summary     282
Inferences Concerning Proportions     285
Estimation of Proportions     285
Hypotheses Concerning One Proportion     292
Hypotheses Concerning Two Proportions     294
Hypotheses Concerning Several Proportions     298
The Analysis of r x c Tables     303
Exercises     305
Summary      309
Final Examinations     313
Final Examination 1     313
Final Examination 2     323
Solutions to Chapter Exercises and Final Exams     335
Bibliography     419
Index     421
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