Statistics and Probability for Engineering Applications with Microsoft Excel

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.9780750676182, 0750676183

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 ExcelIn 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”

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Table of contents :
Contents……Page 5
Preface……Page 11
What’s on the CD-ROM?……Page 13
List of Symbols……Page 15
1.1 Some important terms……Page 17
1.2 What does this book contain?……Page 19
2.1 Fundamental concepts……Page 22
2.2 Basic rules of combining probabilities……Page 27
2.3 Permutations and combinations……Page 45
2.4 More complex problems: Bayes’ Rules……Page 50
3.1 Central location……Page 57
3.2 Variability or spread of the data……Page 60
3.3 Quartiles, deciles, percentiles, and quantiles……Page 67
3.4 Using a computer to calculate summary numbers……Page 71
4.1 Stem-and-leaf displays……Page 79
4.2 Box plots……Page 81
4.4 Continuous data: grouped frequency……Page 82
4.5 Use of computers……Page 91
5 Probability distributions of discrete variables……Page 100
5.1 Probability functions and distribution functions……Page 101
5.2 Expectation and variance……Page 104
5.3 Binomial distribution……Page 117
5.4 Poisson distribution……Page 133
5.5 Extension: other discrete distributions……Page 147
5.6 Relation between probability distributions and frequency distributions……Page 149
6.1 Probability from the probability density function……Page 157
6.2 Expected value and variance……Page 165
6.3 Extension: useful continuous distributions……Page 171
6.4 Extension: reliability……Page 172
7.1 Characteristics……Page 173
7.2 Probablility from the probability density function……Page 174
7.3 Using tables for the normal distribution……Page 177
7.4 Using the computer……Page 189
7.5 Fitting the normal distribution to frequency data……Page 191
7.6 Normal approximation to a binomial distribution……Page 194
7.7 Fitting the normal distribution to cumulative frequency data……Page 200
7.8 Transformation of variables to give a normal distribution……Page 206
8.1 Sampling……Page 213
8.2 Linear combination of independent variables……Page 214
8.3 Variance of sample means……Page 215
8.4 Shape of distribution of samples means: central limit theorem……Page 221
9 Statistical inferences for the Mean……Page 228
9.1 Inferences for the mean when variance is known……Page 229
9.2 Inferences for the mean when variance is estimated from a sample……Page 244
10.1 Inferences for variance……Page 264
10.2 Inferences for proportion……Page 277
11 Introduction to Design of Experiments……Page 288
11.2 Scale of experimentation……Page 289
11.3 One-factor-at-a-time vs. factorial design……Page 290
11.5 Bias due to interfering factors……Page 295
11.6 Fractional factorial designs……Page 304
12 Introduction to Analysis of Variance……Page 310
12.1 One-way analysis of variance……Page 311
12.2 Two-way analysis of variance……Page 320
12.3 Analysis of randomized block design……Page 332
12.4 Concluding remarks……Page 336
13.1 Calculation of the Chi-squared function……Page 340
13.2 Case of equal probabilities……Page 342
13.3 Goodness of fit……Page 343
13.4 Contingency tables……Page 347
14 Regression and Correlation……Page 357
14.1 Simple linear regression……Page 358
14.2 Assumptions and graphical checks……Page 364
14.3 Statistical inferences……Page 368
14.4 Other forms with single input or regressor……Page 377
14.5 Correlation……Page 380
14.6 Extension: introduction to multiple linear regression……Page 383
15.1 Useful reference books……Page 389
15.2 List of selected references……Page 390
A: Tables……Page 392
B: Some properties of Excel useful during the learning process……Page 398
C: Functions useful once the fundamentals are understood……Page 402
D: Answers to some of the problems……Page 403
Engineering Problem-Solver Index……Page 407
Index……Page 409
Limited Warranty and Disclaimer of Liability……Page 416