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: 408
• 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 8
What's on the CD-ROM?......Page 10
List of Symbols......Page 11
1.1 Some important terms......Page 12
1.2 What does this book contain?......Page 14
2.1 Fundamental concepts......Page 17
2.2 Basic rules of combining probabilities......Page 22
2.3 Permutations and combinations......Page 40
2.4 More complex problems: Bayes' Rules......Page 45
3.1 Central location......Page 52
3.2 Variability or spread of the data......Page 55
3.3 Quartiles, deciles, percentiles, and quantiles......Page 62
3.4 Using a computer to calculate summary numbers......Page 66
4.1 Stem-and-leaf displays......Page 74
4.2 Box plots......Page 76
4.4 Continuous data: grouped frequency......Page 77
4.5 Use of computers......Page 86
5 Probability distributions of discrete variables......Page 95
5.1 Probability functions and distribution functions......Page 96
5.2 Expectation and variance......Page 99
5.3 Binomial distribution......Page 112
5.4 Poisson distribution......Page 128
5.5 Extension: other discrete distributions......Page 142
5.6 Relation between probability distributions and frequency distributions......Page 144
6.1 Probability from the probability density function......Page 152
6.2 Expected value and variance......Page 160
6.3 Extension: useful continuous distributions......Page 166
6.4 Extension: reliability......Page 167
7.1 Characteristics......Page 168
7.2 Probablility from the probability density function......Page 169
7.3 Using tables for the normal distribution......Page 172
7.4 Using the computer......Page 184
7.5 Fitting the normal distribution to frequency data......Page 186
7.6 Normal approximation to a binomial distribution......Page 189
7.7 Fitting the normal distribution to cumulative frequency data......Page 195
7.8 Transformation of variables to give a normal distribution......Page 201
8.1 Sampling......Page 208
8.2 Linear combination of independent variables......Page 209
8.3 Variance of sample means......Page 210
8.4 Shape of distribution of samples means: central limit theorem......Page 216
9 Statistical inferences for the Mean......Page 223
9.1 Inferences for the mean when variance is known......Page 224
9.2 Inferences for the mean when variance is estimated from a sample......Page 239
10.1 Inferences for variance......Page 259
10.2 Inferences for proportion......Page 272
11 Introduction to Design of Experiments......Page 283
11.2 Scale of experimentation......Page 284
11.3 One-factor-at-a-time vs. factorial design......Page 285
11.5 Bias due to interfering factors......Page 290
11.6 Fractional factorial designs......Page 299
12 Introduction to Analysis of Variance......Page 305
12.1 One-way analysis of variance......Page 306
12.2 Two-way analysis of variance......Page 315
12.3 Analysis of randomized block design......Page 327
12.4 Concluding remarks......Page 331
13.1 Calculation of the Chi-squared function......Page 335
13.2 Case of equal probabilities......Page 337
13.3 Goodness of fit......Page 338
13.4 Contingency tables......Page 342
14 Regression and Correlation......Page 352
14.1 Simple linear regression......Page 353
14.2 Assumptions and graphical checks......Page 359
14.3 Statistical inferences......Page 363
14.4 Other forms with single input or regressor......Page 372
14.5 Correlation......Page 375
14.6 Extension: introduction to multiple linear regression......Page 378
15.1 Useful reference books......Page 384
15.2 List of selected references......Page 385
A: Tables......Page 387
B: Some properties of Excel useful during the learning process......Page 393
C: Functions useful once the fundamentals are understood......Page 397
D: Answers to some of the problems......Page 398
Engineering Problem-Solver Index......Page 402
Index......Page 404
Limited Warranty and Disclaimer of Liability......Page 408