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: 414
• 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 3
Preface......Page 9
What's on the CD-ROM?......Page 11
List of Symbols......Page 13
1.1 Some important terms......Page 15
1.2 What does this book contain?......Page 17
2.1 Fundamental concepts......Page 20
2.2 Basic rules of combining probabilities......Page 25
2.3 Permutations and combinations......Page 43
2.4 More complex problems: Bayes' Rules......Page 48
3.1 Central location......Page 55
3.2 Variability or spread of the data......Page 58
3.3 Quartiles, deciles, percentiles, and quantiles......Page 65
3.4 Using a computer to calculate summary numbers......Page 69
4.1 Stem-and-leaf displays......Page 77
4.2 Box plots......Page 79
4.4 Continuous data: grouped frequency......Page 80
4.5 Use of computers......Page 89
5 Probability distributions of discrete variables......Page 98
5.1 Probability functions and distribution functions......Page 99
5.2 Expectation and variance......Page 102
5.3 Binomial distribution......Page 115
5.4 Poisson distribution......Page 131
5.5 Extension: other discrete distributions......Page 145
5.6 Relation between probability distributions and frequency distributions......Page 147
6.1 Probability from the probability density function......Page 155
6.2 Expected value and variance......Page 163
6.3 Extension: useful continuous distributions......Page 169
6.4 Extension: reliability......Page 170
7.1 Characteristics......Page 171
7.2 Probablility from the probability density function......Page 172
7.3 Using tables for the normal distribution......Page 175
7.4 Using the computer......Page 187
7.5 Fitting the normal distribution to frequency data......Page 189
7.6 Normal approximation to a binomial distribution......Page 192
7.7 Fitting the normal distribution to cumulative frequency data......Page 198
7.8 Transformation of variables to give a normal distribution......Page 204
8.1 Sampling......Page 211
8.2 Linear combination of independent variables......Page 212
8.3 Variance of sample means......Page 213
8.4 Shape of distribution of samples means: central limit theorem......Page 219
9 Statistical inferences for the Mean......Page 226
9.1 Inferences for the mean when variance is known......Page 227
9.2 Inferences for the mean when variance is estimated from a sample......Page 242
10.1 Inferences for variance......Page 262
10.2 Inferences for proportion......Page 275
11 Introduction to Design of Experiments......Page 286
11.2 Scale of experimentation......Page 287
11.3 One-factor-at-a-time vs. factorial design......Page 288
11.5 Bias due to interfering factors......Page 293
11.6 Fractional factorial designs......Page 302
12 Introduction to Analysis of Variance......Page 308
12.1 One-way analysis of variance......Page 309
12.2 Two-way analysis of variance......Page 318
12.3 Analysis of randomized block design......Page 330
12.4 Concluding remarks......Page 334
13.1 Calculation of the Chi-squared function......Page 338
13.2 Case of equal probabilities......Page 340
13.3 Goodness of fit......Page 341
13.4 Contingency tables......Page 345
14 Regression and Correlation......Page 355
14.1 Simple linear regression......Page 356
14.2 Assumptions and graphical checks......Page 362
14.3 Statistical inferences......Page 366
14.4 Other forms with single input or regressor......Page 375
14.5 Correlation......Page 378
14.6 Extension: introduction to multiple linear regression......Page 381
15.1 Useful reference books......Page 387
15.2 List of selected references......Page 388
A: Tables......Page 390
B: Some properties of Excel useful during the learning process......Page 396
C: Functions useful once the fundamentals are understood......Page 400
D: Answers to some of the problems......Page 401
Engineering Problem-Solver Index......Page 405
Index......Page 407
Limited Warranty and Disclaimer of Liability......Page 414