Statistics and Probability with Applications for Engineers and Scientists

Preface xvii Chapter 1 | Introduction 1 1.1 Designed Experiment 2 1.2 A Survey 5 1.3 An Observational Study 6 1.4 A Set of Historical Data 6 1.5 A Brief Description of What is Covered in This Book 6 PART I Chapter 2 | Describing Data Graphically and Numerically 11 2.1 Getting Started with Statistics 12 2.2 Classification of Various Types of Data 15 2.3 Frequency Distribution Tables for Qualitative and Quantitative Data 17 2.4 Graphical Description of Qualitative and Quantitative Data 25 2.5 Numerical Measures of Quantitative Data 41 2.6 Numerical Measures of Grouped Data 55 2.7 Measures of Relative Position 59 2.8 Box-Whisker Plot 62 2.9 Measures of Association 68 2.10 Case Studies 71 2.11 Using JMP1 73 Review Practice Problems 73 Chapter 3 | Elements of Probability 83 3.1 Introduction 84 3.2 Random Experiments, Sample Spaces, and Events 84 3.3 Concepts of Probability 88 3.4 Techniques of Counting Sample Points 93 3.5 Conditional Probability 98 3.6 Bayes's Theorem 100 3.7 Introducing Random Variables 104 Review Practice Problems 105 Chapter 4 | Discrete Random Variables and Some Important Discrete Probability Distributions 111 4.1 Graphical Descriptions of Discrete Distributions 112 4.2 Mean and Variance of a Discrete Random Variable 113 4.3 The Discrete Uniform Distribution 117 4.4 The Hypergeometric Distribution 119 4.5 The Bernoulli Distribution 122 4.6 The Binomial Distribution 123 4.7 The Multinomial Distribution 126 4.8 The Poisson Distribution 128 4.9 The Negative Binomial Distribution 132 4.10 Some Derivations and Proofs (Optional) 135 4.11 A Case Study 135 4.12 Using JMP 135 Review Practice Problems 136 Chapter 5 | Continuous Random Variables and Some Important Continuous Probability Distributions 143 5.1 Continuous Random Variables 144 5.2 Mean and Variance of Continuous Random Variables 146 5.3 Chebychev's Inequality 151 5.4 The Uniform Distribution 152 5.5 The Normal Distribution 157 5.6 Distribution of Linear Combination of Independent Normal Variables 165 5.7 Approximation of the Binomial and Poisson Distribution by the Normal Distribution 169 5.8 A Test of Normality 171 5.9 Probability Models Commonly Used in Reliability Theory 175 5.10 A Case Study 191 5.11 Using JMP 192 Review Practice Problems 192 Chapter 6 | Distribution of Functions of Random Variables 199 6.1 Introduction 200 6.2 Distribution Functions of Two Random Variables 200 6.3 Extension to Several Random Variables 214 6.4 The Moment-Generating Function Revisited 214 Review Practice Problems 218 Chapter 7 | Sampling Distributions 223 7.1 Random Sampling 224 7.2 The Sampling Distribution of the Mean 228 7.3 Sampling from a Normal Population 234 7.4 Order Statistics 247 7.5 Using JMP 247 Review Practice Problems 247 Chapter 8 | Estimation of Population Parameters 251 8.1 Introduction 252 8.2 Point Estimators for the Population Mean and Variance 252 8.3 Interval Estimators for the Mean m of a Normal Population 262 8.4 Interval Estimators for the Difference of Means of Two Normal Populations 272 8.5 Interval Estimators for the Variance of a Normal Population 280 8.6 Interval Estimator for the Ratio of Variances of Two Normal Populations 284 8.7 Point and Interval Estimators for the Parameters of Binomial Populations 288 8.8 Determination of Sample Size 294 8.9 Some Supplemental Information 298 8.10 A Case Study 298 8.11 Using JMP 299 Review Practice Problems 299 Chapter 9 | Hypothesis Testing 307 9.1 Introduction 308 9.2 Basic Concepts of Testing a Statistical Hypothesis 308 9.3 Tests Concerning the Mean of a Normal Population Having Known Variance 312 9.4 Tests Concerning the Mean of a Normal Population Having Unknown Variance 324 9.5 Large Sample Theory 330 9.6 Tests Concerning the Difference of Means of Two Populations Having Distributions with Known Variances 332 9.7 Tests Concerning the Difference of Means of Two Populations Having Normal Distributions with Unknown Variances 339 9.8 Testing Population Proportions 349 9.9 Tests Concerning the Variance of a Normal Population 355 9.10 Tests Concerning the Ratio of Variances of Two Normal Populations 358 9.11 Testing of Statistical Hypotheses Using Confidence Intervals 362 9.12 Sequential Tests of Hypotheses 367 9.13 Case Studies 374 9.14 Using JMP 375 Review Practice Problems 375 PART II Chapter 10 | Elements of Reliability Theory 389 10.1 The Reliability Function 390 10.2 Estimation: Exponential Distribution 399 10.3 Hypothesis Testing: Exponential Distribution 406 10.4 Estimation: Weibull Distribution 407 10.5 Case Studies 414 10.6 Using JMP 416 Review Practice Problems 416 Chapter 11 | Statistical Quality Control--Phase I Control Charts 419 11.1 Basic Concepts of Quality and Its Benefits 420 11.2 What a Process Is and Some Valuable Tools 420 11.3 Common and Assignable Causes 427 11.4 Control Charts 429 11.5 Control Charts for Variables 434 11.6 Control Charts for Attributes 448 11.7 Process Capability 468 11.8 Case Studies 470 11.9 Using JMP 472 Review Practice Problems 472 Chapter 12 | Statistical Quality Control--Phase II Control Charts 479 12.1 Introduction 480 12.2 Basic Concepts of CUSUM Control Chart 480 12.3 Designing a CUSUM Control Chart 483 12.4 The Moving Average (MA) Control Chart 495 12.5 The Exponentially Weighted Moving Average (EWMA) Control Chart 499 12.6 Case Studies 504 12.7 Using JMP 505 Review Practice Problems 506 Chapter 13 | Analysis of Categorical Data 509 13.1 Introduction 509 13.2 The Chi-Square Goodness-of-Fit Test 510 13.3 Contingency Tables 517 13.4 Chi-Square Test for Homogeneity 525 13.5 Comments on the Distribution of the Lack-of-Fit Statistics 528 13.6 Case Studies 529 Review Practice Problems 531 Chapter 14 | Nonparametric Tests 537 14.1 Introduction 537 14.2 The Sign Test 538 14.3 Mann-Whitney (Wilcoxon) W Test for Two Samples 548 14.4 Runs Test 551 14.5 Spearman Rank Correlation 556 14.6 Using JMP 559 Review Practice Problems 559 Chapter 15 | Simple Linear Regression Analysis 565 15.1 Introduction 566 15.2 Fitting the Simple Linear Regression Model 567 15.3 Unbiased Estimator of s2 578 15.4 Further Inferences Concerning Regression Coefficients (b0, b1), E(Y), and Y 580 15.5 Tests of Hypotheses for b0 and b1 590 15.6 Analysis of Variance Approach to Simple Linear Regression Analysis 596 15.7 Residual Analysis 601 15.8 Transformations 609 15.9 Inference About r 615 15.10 A Case Study 618 15.11 Using JMP 619 Review Practice Problems 619 Chapter 16 | Multiple Linear Regression Analysis 627 16.1 Introduction 628 16.2 Multiple Linear Regression Models 628 16.3 Estimation of Regression Coefficients 632 16.4 Multiple Linear Regression Model Using Quantitative and Qualitative Predictor Variables 646 16.5 Standardized Regression Coefficients 658 16.6 Building Regression Type Prediction Models 662 16.7 Residual Analysis and Certain Criteria for Model Selection 665 16.8 Logistic Regression 672 16.9 Case Studies 676 16.10 Using JMP 677 Review Practice Problems 678 Chapter 17 | Analysis of Variance 685 17.1 Introduction 686 17.2 The Design Models 686 17.3 One-Way Experimental Layouts 689 17.4 Randomized Complete Block Designs 710 17.5 Two-Way Experimental Layouts 722 17.6 Latin Square Designs 736 17.7 Random-Effects and Mixed-Effects Models 742 17.8 A Case Study 752 17.9 Using JMP 753 Review Practice Problems 753 Chapter 18 | The 2k Factorial Designs 765 18.1 Introduction 766 18.2 The Factorial Designs 766 18.3 The 2k Factorial Design 768 18.4 Unreplicated 2k Factorial Designs 776 18.5 Blocking in the 2k Factorial Design 782 18.6 The 2k Fractional Factorial Designs 790 18.7 Case Studies 799 18.8 Using JMP 801 Review Practice Problems 801 Chapter 19 | Response Surfaces This chapter is not included in text, but is available for download via the book's website: www.wiley.com/go/statsforengineers Appendices 807 Appendix A | Statistical Tables 809 Appendix B | Answers to Selected Problems 845 Appendix C | Bibliography 863 Index 867