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Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. NINTH EdITIoN Probability and Statistics for Engineering and the Sciences Jay Devore California Polytechnic State University, San Luis Obispo Australia Brazil Mexico Singapore United Kingdom United States Copyright 2016 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. Probability and Statistics for Engineering © 2016, 2012, 2009, Cengage Learning and the Sciences, Ninth Edition WCN: 02-200-203 Jay L. Devore ALL RIGHTS RESERVED. 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Contents 1 Overview and Descriptive Statistics Introduction 1 1.1 Populations, Samples, and Processes 3 1.2 Pictorial and Tabular Methods in Descriptive Statistics 13 1.3 Measures of Location 29 1.4 Measures of Variability 36 Supplementary Exercises 47 Bibliography 51 2 Probability Introduction 52 2.1 Sample Spaces and Events 53 2.2 Axioms, Interpretations, and Properties of Probability 58 2.3 Counting Techniques 66 2.4 Conditional Probability 75 2.5 Independence 85 Supplementary Exercises 91 Bibliography 94 3 Discrete Random Variables and Probability Distributions Introduction 95 3.1 Random Variables 96 3.2 Probability Distributions for Discrete Random Variables 99 3.3 Expected Values 109 3.4 The Binomial Probability Distribution 117 3.5 Hypergeometric and Negative Binomial Distributions 126 3.6 The Poisson Probability Distribution 131 Supplementary Exercises 137 Bibliography 140 vii viii Contents 4 Continuous Random Variables and Probability Distributions Introduction 141 4.1 Probability Density Functions 142 4.2 Cumulative Distribution Functions and Expected Values 147 4.3 The Normal Distribution 156 4.4 The Exponential and Gamma Distributions 170 4.5 Other Continuous Distributions 177 4.6 Probability Plots 184 Supplementary Exercises 193 Bibliography 197 5 Joint Probability Distributions and Random Samples Introduction 198 5.1 Jointly Distributed Random Variables 199 5.2 Expected Values, Covariance, and Correlation 213 5.3 Statistics and Their Distributions 220 5.4 The Distribution of the Sample Mean 230 5.5 The Distribution of a Linear Combination 238 Supplementary Exercises 243 Bibliography 246 6 Point Estimation Introduction 247 6.1 Some General Concepts of Point Estimation 248 6.2 Methods of Point Estimation 264 Supplementary Exercises 274 Bibliography 275 7 Statistical Intervals Based on a Single Sample Introduction 276 7.1 Basic Properties of Confidence Intervals 277 7.2 Large-Sample Confidence Intervals for a Population Mean and Proportion 285 Contents ix 7.3 Intervals Based on a Normal Population Distribution 295 7.4 Confidence Intervals for the Variance and Standard Deviation of a Normal Population 304 Supplementary Exercises 307 Bibliography 309 8 Tests of Hypotheses Based on a Single Sample Introduction 310 8.1 Hypotheses and Test Procedures 311 8.2 z Tests for Hypotheses about a Population Mean 326 8.3 The One-Sample t Test 335 8.4 Tests Concerning a Population Proportion 346 8.5 Further Aspects of Hypothesis Testing 352 Supplementary Exercises 357 Bibliography 360 9 Inferences Based on Two Samples Introduction 361 9.1 z Tests and Confidence Intervals for a Difference Between Two Population Means 362 9.2 The Two-Sample t Test and Confidence Interval 374 9.3 Analysis of Paired Data 382 9.4 Inferences Concerning a Difference Between Population Proportions 391 9.5 Inferences Concerning Two Population Variances 399 Supplementary Exercises 403 Bibliography 408 10 The Analysis of Variance Introduction 409 10.1 Single-Factor ANOVA 410 10.2 Multiple Comparisons in ANOVA 420 10.3 More on Single-Factor ANOVA 426 Supplementary Exercises 435 Bibliography 436 x Contents 11 Multifactor Analysis of Variance Introduction 437 11.1 Two-Factor ANOVA with K 5 1 438 ij 11.2 Two-Factor ANOVA with K . 1 451 ij 11.3 Three-Factor ANOVA 460 11.4 2p Factorial Experiments 469 Supplementary Exercises 483 Bibliography 486 12 Simple Linear Regression and Correlation Introduction 487 12.1 The Simple Linear Regression Model 488 12.2 Estimating Model Parameters 496 12.3 Inferences About the Slope Parameter b 510 1 12.4 Inferences Concerning m and Y ?x* the Prediction of Future Y Values 519 12.5 Correlation 527 Supplementary Exercises 437 Bibliography 541 13 Nonlinear and Multiple Regression Introduction 542 13.1 Assessing Model Adequacy 543 13.2 Regression with Transformed Variables 550 13.3 Polynomial Regression 562 13.4 Multiple Regression Analysis 572 13.5 Other Issues in Multiple Regression 595 Supplementary Exercises 610 Bibliography 618 14 Goodness-of-Fit Tests and Categorical Data Analysis Introduction 619 14.1 Goodness-of-Fit Tests When Category Probabilities Are Completely Specified 620 14.2 Goodness-of-Fit Tests for Composite Hypotheses 627 14.3 Two-Way Contingency Tables 639