Statistics and Probability for Engineering Applications with Microsoft Excel

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 Audience: Engineers in the entire engineering spectrum: electronics/electrical, mechanical, chemical, and civil engineering; Engineering students; Scientists needing to use applied statistical methods; Engineering technicians and technologists U.S. Dept. of Labor recent stats: Electrical and electronics engineers: 310,000 Computer hardware engineers: 60,000 Electrical and electronics engineering technicians: 262,000 Computer applied software engineers: 380,000 IEEE US membership is 240,000, including students Approx. 25,000 electrical/electronics engineers graduate in U.S. each year, and 15,000 computer science/computer engineering graduates source: Prentice-Hall U.S. imports approx. 100,000 foreign engineers each year American Society of Mechanical Engineers - 125,000 members American Institute of Chemical Engineers - 50,000 members American Society of Civil Engineers - 125,000 members. 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 Statistics and Probability for Engineering Applications provides a complete discussion of all the major topics typically covered in a college engineering statistics course. This textbook minimizes the derivations and mathematical theory, focusing instead on the information and techniques most needed and used in engineering applications. It is filled with practical techniques directly applicable on the job. Written by an experienced industry engineer and statistics professor, this book makes learning statistical methods easier for today's student. This book can be read sequentially like a normal textbook, but 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. Each new concept is clearly and briefly described, whenever possible by relating it to previous topics. Then the student is given carefully chosen examples to deepen understanding of the basic ideas and how they are applied in engineering. The examples and case studies are taken from real-world engineering problems and use real data. A number of practice problems are provided for each section, with answers in the back for selected problems. This book will appeal to engineers in the entire engineering spectrum (electronics/electrical, mechanical, chemical, and civil engineering); engineering students and students taking computer science/computer engineering graduate courses; scientists needing to use applied statistical methods; and engineering technicians and technologists. * Filled with practical techniques directly applicable on the job* Contains hundreds of solved problems and case studies, using real data sets* Avoids unnecessary theory Makes statistical methods easier and accessible to engineers. This book points the reader to the topics and sections pertinent to a particular type of statistical problem. It includes a CD-ROM that contains the Excel data sets for the examples and case studies given in the book, along with other statistical tools and software