理工科概率统计 第7版PDF电子书下载

1 Introduction to Statistics and Data Analysis 1

1.1 Overview:Statistical Inference,Samples,Populations,and Experimental Design 1

1.2　The Role of Probability 4

1.3 Sampling Procedures;Collection of Data 7

1.4 Measures of Location:The Sample Mean 9

1.5 Measures of Variability 11

1.6　Discrete and Continuous Data 14

1.7 Statistical Modeling,Scientific Inspection,and Graphical Diagnostics 14

Preface 15

Contents 15

1.8 Graphical Methods and Data Description 16

2.1 Sample Space 22

2 Probability 22

2.2 Events 25

2.3 Counting Sample Points 31

2.4　Probability of an Event 39

2.5 Additive Rules 43

2.6 Conditional Probability 47

2.7 Multiplicative Rules 50

2.8 Bayes'Rule 57

Review Exercises 61

3 Random Variables and Probability Distributions 63

3.1 Concept of a Random Variable 63

3.2　Discrete Probability Distributions 65

3.3 Continuous Probability Distributions 69

3.4 Joint Probability Distributions 74

Review Exercises 86

4　Mathematical Expectation 88

4.1 Mean of a Random Variable 88

4.2 Variance and Covariance 95

4.3 Means and Variances of Linear Combinations of Random Variables 103

4.4 Chebyshev's Theorem 110

Review Exercises 114

5 Some Discrete Probability Distributions 115

5.1 Introduction 115

5.2　Discrete Uniform Distribution 116

5.3 Binomial and Multinomial Distributions 117

5.4　Hypergeometric Distribution 126

5.5 Negative Binomial and Geometric Distributions 132

5.6　Poisson Distribution and the Poisson Process 135

Review Exercises 140

6 Some Continuous Probability Distributions 142

6.1 Continuous Uniform Distribution 142

6.2 Normal Distribution 143

6.3 Areas Under the Normal Curve 147

6.4 Applications of the Normal Distribution 152

6.5 Normal Approximation to the Binomial 158

6.6 Gamma and Exponential Distributions 165

6.7 Applications of the Exponential and Gamma Distributions 168

6.8 Chi-Squared Distribution 170

6.9 Lognormal Distribution 171

6.10 Weibull Distribution 172

Review Exercises 175

7 Functions of Random Variables（Optional） 177

7.1 Introduction 177

7.2 Transformations of Variables 177

7.3 Moments and Moment-Generating Functions 186

8 Fundamental Sampling Distributions and Data Descriptions 194

8.1 Random Sampling 194

8.2 Some Important Statistics 197

8.3 Data Displays and Graphical Methods 201

8.4 Sampling Distributions 208

8.5 Sampling Distribution of Means 209

8.6 Sampling Distribution of S2 216

8.7 t-Distribution 219

8.8 F-Distribution 224

Review Exercises 228

9 One-and Two-Sample Estimation Problems 230

9.1 Introduction 230

9.2 Statistical Inference 230

9.3 Classical Methods of Estimation 231

9.4 Single Sample:Estimating the Mean 234

9.5 Standard Error of a Point Estimate 240

9.6 Prediction Interval 241

9.7 Tolerance Limits 243

9.8 Two Samples:Estimating the Difference Between Two Means 246

9.9 Paired Observations 253

9.10 Single Sample:Estimating a Proportion 257

9.11 Two Samples:Estimating the Difference Between Two Proportions 261

9.12 Single Sample:Estimating the Variance 264

9.13 Two Samples:Estimating the Ratio of Two Variances 265

9.14 Bayesian Methods of Estimation（Optional） 268

9.15 Maximum Likelihood Estimation（Optional） 275

Review Exercises 281

10.1 Statistical Hypotheses:General Concepts 284

10 One-and Two-Sample Tests of Hypotheses 284

10.2 Testing a Statistical Hypothesis 286

10.3 One-and Two-Tailed Tests 294

10.4 The Use of P-Values for Decision Making 295

10.5 Single Sample:Tests Concerning a Single Mean（Variance Known） 300

10.6 Relationship to Confidence Interval Estimation 303

10.7 Single Sample:Tests on a Single Mean（Variance Unknown） 304

10.8 Two Samples:Tests on Two Means 307

10.9 Choice of Sample Size for Testing Means 312

10.10 Graphical Methods for Comparing Means 316

10.11 One Sample:Test on a Single Proportion 323

10.12 Two Samples:Tests on Two Proportions 326

10.13 One-and Two-Sample Tests Concerning Variances 328

10.14 Goodness-of-Fit Test 333

10.15 Test for Independence（Categorical Data） 336

10.16 Test for Homogeneity 339

10.17 Testing for Several Proportions 340

10.18 Two-Sample Case Study 342

Review Exercises 347

11 Simple Linear Regression and Correlation 350

11.1 Introduction to Linear Regression 350

11.2 Simple Linear Regression 351

11.3 Least Squares and The Fitted Model 355

11.4 Properties of the Least Squares Estimators 360

11.5 Inferences Concerning the Regression Coefficients 363

11.6 Prediction 368

11.7 Choice of a Regression Model 372

11.8 Analysis-of-Variance Approach 373

11.9 Test for Linearity of Regression:Data with Repeated Observations 375

11.10 Data Plots and Transformations 383

11.11 Simple Linear Regression Case Study 387

11.12 Correlation 390

Review Exercises 396

12 Multiple Linear Regression and Certain Nonlinear Regression Models 400

12.1 Introduction 400

12.2 Estimating the Coefficients 401

12.3 Linear Regression Model Using Matrices（Optional） 404

12.4 Properties of the Least Squares Estimators 411

12.5 Inferences in Multiple Linear Regression 413

12.6 Choice of a Fitted Model Through Hypothesis Testing 420

12.7 Special Case of Orthogonality（Optional） 423

12.8 Categorical or Indicator Variables 427

12.9 Sequential Methods for Model Selection 432

12.10 Study of Residuals and Violation of Assumptions 438

12.11 Cross Validation,Cp,and Other Criteria for Model Selection 442

12.12 Special Nonlinear Models for Nonideal Conditions 452

Review Exercises 456

13.1 Analysis-of-Variance Technique 461

13 One-Factor Experiments:General 461

13.2 The Strategy of Experimental Design 463

13.3 One-Way Analysis of Variance:Completely Randomized Design 463

13.4 Tests for the Equality of Several Variances 469

13.5 Single-Degree-of-Freedom Comparisons 473

13.6 Multiple Comparisons 477

13.7 Comparing Treatments with a Control 481

13.8 Comparing a Set of Treatments in Blocks 486

13.9 Randomized Complete Block Designs 487

13.10 Graphical Methods and Further Diagnostics 494

13.11 Latin Squares（Optional） 496

13.12 Random Effects Models 502

13.13 Power of Analysis-of-Variance Tests 507

13.14 Case Study 511

Review Exercises 515

14 Factorial Experiments（Two or More Factors） 519

14.1 Introduction 519

14.2 Interaction and the Two-Factor Experiment 521

14.3 Two-Factor Analysis of Variance 522

14.4 Graphical Analysis in the Two-Factor Problem 530

14.5 Three-Factor Experiments 535

14.6 Model Ⅱ and Ⅲ Factorial Experiments 545

14.7 Choice of Sample Size 549

Review Exercises 552

15.1 Introduction 555

15 2k Factorial Experiments and Fractions 555

15.2 Analysis of Variance and the Calculation of Effects 556

15.3 Nonreplicated 2k Factorial Experiment 560

15.4 Injection Molding Case Study 561

15.5 Factorial Experiments in Incomplete Blocks 567

15.6 Partial Confounding 572

15.7 Factorial Experiments in a Regression Setting 575

15.8 The Orthogonal Design 579

15.9 Fractional Factorial Experiments 582

15.10 Analysis of Fractional Factorial Experiments 585

15.11 Higher Fractions and Screening Designs 589

15.12 Construction of Resolution Ⅲ and Ⅳ Designs with 8,16,and 32 Design Points 590

15.13　Other Two-Level Resolution Ⅲ Designs;The Plackett-Burman Designs 591

15.14　Taguchi's Robust Parameter Design 592

Review Exercises 598

16　Nonparametric Statistics 600

16.1 Nonparametric Tests 600

16.2 Sign Test 601

16.3 Signed-Rank Test 605

16.4 Rank-Sum Test 610

16.5 Kruskal-Wallis Test 613

16.6 Runs Test 616

16.7 Tolerance Limits 619

16.8 Rank Correlation Coefficient 620

Review Exercises 624

17 Statistical Quality Control 625

17.1 Introduction 625

17.2 Nature of the Control Limits 627

17.3 Purposes of the Control Chart 627

17.4 Control Charts for Variables 628

17.5 Control Charts for Attributes 643

17.6 Cusum Control Charts 649

Review Exercises 653

Bibliography 656

Appendix:Statistical Tables and Proofs 659

Answers to Odd-Numbered Exercises 715

Index 726