Statistics and Probability for Engineering Applications

✍ Scribed by William DeCoursey William DeCoursey Ph.D. is a chemical engineer who has taught statistics and probability to engineering students for over 15 years at the University of Saskatchewan.

• Publisher: Newnes
• Year: 2003
• Tongue: English
• Leaves: 417
• Edition: Book and CD-Rom
• Category: Library

✦ Synopsis

More than ever, American industry- especially the semiconductor industry- is using statistical methods to improve its competitive edge in the world market. It is becoming more imperative that graduate engineers have solid statistical know-how, yet engineers in industry typically are not well-prepared to use statistics and they are fuzzy about how to apply statistical tools and techniques. This valuable reference makes statistical methods easier and more accessible to engineers. Although the book can be read sequentially, like a normal textbook, it is designed to be used as a handbook, pointing the reader to the topics and sections pertinent to a particular type of statistical problem. It contains the following features: * Covers all major topics treated in a standard college engineering statistics course, but minimizes the mathematical derivations and focuses on practical applications * Uses real data sets/case studies taken from electronics, electrical engineering, and other engineering fields, such as mechanical and chemical engineering * Contains numerous software examples using the powerful statistical functions of Excel In addition, the book provides an "engineering problem solver" section that directs the reader to the relevant section of the book for the problem they are trying to solve. The accompanying CD-ROM contains the Excel data sets for the examples and case studies given in the book, along with other statistical tools and software. * Filled with practical techniques directly applicable on the job * Contains hundreds of solved problems and case studies, using real data sets * Avoids unnecessary theory

✦ Table of Contents

Contents......Page 6
Preface......Page 12
What's on the CD-ROM?......Page 14
List of Symbols......Page 16
1.1 Some important terms......Page 18
1.2 What does this book contain?......Page 20
2.1 Fundamental concepts......Page 23
2.2 Basic rules of combining probabilities......Page 28
2.3 Permutations and combinations......Page 46
2.4 More complex problems: Bayes' Rules......Page 51
3.1 Central location......Page 58
3.2 Variability or spread of the data......Page 61
3.3 Quartiles, deciles, percentiles, and quantiles......Page 68
3.4 Using a computer to calculate summary numbers......Page 72
4.1 Stem-and-leaf displays......Page 80
4.2 Box plots......Page 82
4.4 Continuous data: grouped frequency......Page 83
4.5 Use of computers......Page 92
5 Probability distributions of discrete variables......Page 101
5.1 Probability functions and distribution functions......Page 102
5.2 Expectation and variance......Page 105
5.3 Binomial distribution......Page 118
5.4 Poisson distribution......Page 134
5.5 Extension: other discrete distributions......Page 148
5.6 Relation between probability distributions and frequency distributions......Page 150
6.1 Probability from the probability density function......Page 158
6.2 Expected value and variance......Page 166
6.3 Extension: useful continuous distributions......Page 172
6.4 Extension: reliability......Page 173
7.1 Characteristics......Page 174
7.2 Probablility from the probability density function......Page 175
7.3 Using tables for the normal distribution......Page 178
7.4 Using the computer......Page 190
7.5 Fitting the normal distribution to frequency data......Page 192
7.6 Normal approximation to a binomial distribution......Page 195
7.7 Fitting the normal distribution to cumulative frequency data......Page 201
7.8 Transformation of variables to give a normal distribution......Page 207
8.1 Sampling......Page 214
8.2 Linear combination of independent variables......Page 215
8.3 Variance of sample means......Page 216
8.4 Shape of distribution of samples means: central limit theorem......Page 222
9 Statistical inferences for the Mean......Page 229
9.1 Inferences for the mean when variance is known......Page 230
9.2 Inferences for the mean when variance is estimated from a sample......Page 245
10.1 Inferences for variance......Page 265
10.2 Inferences for proportion......Page 278
11 Introduction to Design of Experiments......Page 289
11.2 Scale of experimentation......Page 290
11.3 One-factor-at-a-time vs. factorial design......Page 291
11.5 Bias due to interfering factors......Page 296
11.6 Fractional factorial designs......Page 305
12 Introduction to Analysis of Variance......Page 311
12.1 One-way analysis of variance......Page 312
12.2 Two-way analysis of variance......Page 321
12.3 Analysis of randomized block design......Page 333
12.4 Concluding remarks......Page 337
13.1 Calculation of the Chi-squared function......Page 341
13.2 Case of equal probabilities......Page 343
13.3 Goodness of fit......Page 344
13.4 Contingency tables......Page 348
14 Regression and Correlation......Page 358
14.1 Simple linear regression......Page 359
14.2 Assumptions and graphical checks......Page 365
14.3 Statistical inferences......Page 369
14.4 Other forms with single input or regressor......Page 378
14.5 Correlation......Page 381
14.6 Extension: introduction to multiple linear regression......Page 384
15.1 Useful reference books......Page 390
15.2 List of selected references......Page 391
A: Tables......Page 393
B: Some properties of Excel useful during the learning process......Page 399
C: Functions useful once the fundamentals are understood......Page 403
D: Answers to some of the problems......Page 404
Engineering Problem-Solver Index......Page 408
Index......Page 410
Limited Warranty and Disclaimer of Liability......Page 417