Engineering statistics

* Concise And Complete Coverage Of Probability. * Thorough Coverage Of Regression Modeling, Design Of Engineering Experiments, And Statistical Process Control. * Wide Range Of Problem Levels. booknews the Authors Have Made A Selection And Revision From Montgomery And Runger's More Substantial To Produce The Present Text, Which Is Designed To Serve A One-semester Course For Undergraduate Engineering Students Who Have Had At Least One Semester Of Calculus. Meant For An Applied Course, The Text Is Designed To Be Used In Conjunction With Model- Building And The Computer (by Using Minitab, Statgraphics And Excel). All Three Authors Teach At Arizona State University. Annotation C. Book News, Inc., Portland, Or (booknews.com) Cover......Page 1 Title Page......Page 7 Copyright......Page 8 About the Authors......Page 11 Preface......Page 12 Contents......Page 22 CHAPTER 1 The Role of Statistics in Engineering......Page 25 1-1 The Engineering Method and Statistical Thinking......Page 26 1-2 Collecting Engineering Data......Page 30 1-2.1 Retrospective Study......Page 31 1-2.2 Observational Study......Page 32 1-2.3 Designed Experiments......Page 33 1-2.4 Random Samples......Page 36 1-3 Mechanistic and Empirical Models......Page 39 1-4 Observing Processes Over Time......Page 41 CHAPTER 2 Data Summary and Presentation......Page 47 2-1 Data Summary and Display......Page 48 2-2 Stem-and-Leaf Diagram......Page 53 2-3 Histograms......Page 58 2-4 Box Plot......Page 63 2-5 Time Series Plots......Page 65 2-6 Multivariate Data......Page 70 CHAPTER 3 Random Variables and Probability Distributions......Page 81 3-1 Introduction......Page 82 3-2 Random Variables......Page 84 3-3 Probability......Page 86 3-4.1 Probability Density Function......Page 90 3-4.2 Cumulative Distribution Function......Page 92 3-4.3 Mean and Variance......Page 94 3-5.1 Normal Distribution......Page 98 3-5.2 Lognormal Distribution......Page 108 3-5.4 Weibull Distribution......Page 110 3-5.5 Beta Distribution......Page 112 3-6.1 Normal Probability Plots......Page 116 3-6.2 Other Probability Plots......Page 118 3-7.1 Probability Mass Function......Page 121 3-7.2 Cumulative Distribution Function......Page 122 3-7.3 Mean and Variance......Page 123 3-8 Binomial Distribution......Page 126 3-9.1 Poisson Distribution......Page 133 3-9.2 Exponential Distribution......Page 137 3-10 Normal Approximation to the Binomial and Poisson Distributions......Page 143 3-11.1 Joint Distributions......Page 147 3-11.2 Independence......Page 148 3-12 Functions of Random Variables......Page 153 3-12.1 Linear Functions of Independent Random Variables......Page 154 3-12.2 Linear Functions of Random Variables That Are Not Independent......Page 155 3-12.3 Nonlinear Functions of Independent Random Variables......Page 157 3-13 Random Samples, Statistics, and the Central Limit Theorem......Page 160 CHAPTER 4 Decision Making for a Single Sample......Page 172 4-1 Statistical Inference......Page 173 4-2 Point Estimation......Page 174 4-3.1 Statistical Hypotheses......Page 180 4-3.2 Testing Statistical Hypotheses......Page 182 4-3.3 P-Values in Hypothesis Testing......Page 188 4-3.4 One-Sided and Two-Sided Hypotheses......Page 190 4-3.5 General Procedure for Hypothesis Testing......Page 191 4-4.1 Hypothesis Testing on the Mean......Page 193 4-4.2 Type II Error and Choice of Sample Size......Page 197 4-4.4 Some Practical Comments on Hypothesis Testing......Page 201 4-4.5 Confidence Interval on the Mean......Page 202 4-4.6 General Method for Deriving a Confidence Interval......Page 208 4-5 Inference on the Mean of a Population, Variance Unknown......Page 210 4-5.1 Hypothesis Testing on the Mean......Page 211 4-5.2 Type II Error and Choice of Sample Size......Page 217 4-5.3 Confidence Interval on the Mean......Page 219 4-6.1 Hypothesis Testing on the Variance of a Normal Population......Page 223 4-6.2 Confidence Interval on the Variance of a Normal Population......Page 227 4-7.1 Hypothesis Testing on a Binomial Proportion......Page 229 4-7.2 Type II Error and Choice of Sample Size......Page 232 4-7.3 Confidence Interval on a Binomial Proportion......Page 234 4-8.1 Prediction Interval......Page 240 4-8.2 Tolerance Intervals for a Normal Distribution......Page 241 4-10 Testing for Goodness of Fit......Page 243 CHAPTER 5 Decision Making for Two Samples......Page 254 5-1 Introduction......Page 255 5-2 Inference on the Means of Two Populations, Variances Known......Page 256 5-2.1 Hypothesis Testing on the Difference in Means, Variances Known......Page 257 5-2.2 Type II Error and Choice of Sample Size......Page 258 5-2.3 Confidence Interval on the Difference in Means, Variances Known......Page 259 5-3.1 Hypothesis Testing on the Difference in Means......Page 263 5-3.2 Type II Error and Choice of Sample Size......Page 270 5-3.3 Confidence Interval on the Difference in Means......Page 271 5-4 The Paired t-Test......Page 276 5-5.1 Hypothesis Testing on the Ratio of Two Variances......Page 283 5-5.2 Confidence Interval on the Ratio of Two Variances......Page 287 5-6.1 Hypothesis Testing on the Equality of Two Binomial Proportions......Page 289 5-6.2 Type II Error and Choice of Sample Size......Page 292 5-6.3 Confidence Interval on the Difference in Binomial Proportions......Page 293 5-7 Summary Tables for Inference Procedures for Two Samples......Page 295 5-8.1 Completely Randomized Experiment and Analysis of Variance......Page 296 5-8.2 Randomized Complete Block Experiment......Page 305 CHAPTER 6 Building Empirical Models......Page 322 6-1 Introduction to Empirical Models......Page 323 6-2.1 Least Squares Estimation......Page 328 6-2.2 Testing Hypotheses in Simple Linear Regression......Page 336 6-2.3 Confidence Intervals in Simple Linear Regression......Page 339 6-2.4 Prediction of a Future Observation......Page 342 6-2.5 Checking Model Adequacy......Page 343 6-2.6 Correlation and Regression......Page 346 6-3.1 Estimation of Parameters in Multiple Regression......Page 350 6-3.2 Inferences in Multiple Regression......Page 355 6-3.3 Checking Model Adequacy......Page 360 6-4.1 Polynomial Models......Page 368 6-4.2 Categorical Regressors......Page 370 6-4.3 Variable Selection Techniques......Page 372 CHAPTER 7 Design of Engineering Experiments......Page 384 7-1 The Strategy of Experimentation......Page 385 7-2 Factorial Experiments......Page 386 7-3 2k Factorial Design......Page 389 7-3.1 22 Design......Page 390 7-3.2 Statistical Analysis......Page 392 7-3.3 Residual Analysis and Model Checking......Page 398 7-3.4 2k Design for k ≥ 3 Factors......Page 400 7-3.5 Single Replicate of a 2k Design......Page 406 7-4.1 Addition of Center Points......Page 414 7-4.2 Blocking and Confounding......Page 417 7-5.1 One-Half Fraction of a 2k Design......Page 422 7-5.2 Smaller Fractions: 2K−P Fractional Factorial Designs......Page 428 7-6 Response Surface Methods and Designs......Page 438 7-6.1 Method of Steepest Ascent......Page 440 7-6.2 Analysis of a Second-Order Response Surface......Page 442 7-7 Factorial Experiments With More Than Two Levels......Page 448 CHAPTER 8 Statistical Process Control......Page 462 8-1 Quality Improvement and Statistical Process Control......Page 463 8-2.1 Basic Principles......Page 464 8-2.2 Design of a Control Chart......Page 468 8-2.3 Rational Subgroups......Page 470 8-2.4 Analysis of Patterns on Control Charts......Page 471 8-3 X and R Control Charts......Page 473 8-4 Control Charts For Individual Measurements......Page 480 8-5 Process Capability......Page 485 8-6.1 P Chart (Control Chart for Proportions) and nP Chart......Page 489 8-6.2 U Chart (Control Chart for Average Number of Defects per Unit) and C Chart......Page 491 8-7 Control Chart Performance......Page 494 8-8 Measurement Systems Capability......Page 497 APPENDICES......Page 507 APPENDIX A: Statistical Tables and Charts......Page 509 APPENDIX B: Bibliography......Page 524 APPENDIX C: Answers to Selected Exercises......Page 526 INDEX......Page 535 Covering all major aspects of modern engineering statistics, this book explains descriptive statistics, statistical test and confidence intervals for one and two samples, building regression models, designing and analyzing engineering experiments, and more. All examples are based on real-world applications of statistics in engineering. Gives a treatment of engineering statistics, focusing on how statistics is integrated into the engineering problem-solving process. This work covers all major aspects of engineering statistics, including descriptive statistics, statistical test and confidence intervals for one and two samples, building regression models, and more