理工科概率统计 第7版2025|PDF|Epub|mobi|kindle电子书版本百度云盘下载

理工科概率统计 第7版PDF格式电子书版下载

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1 Introduction to Statistics and Data Analysis1

1.1 Overview:Statistical Inference,Samples,Populations,and Experimental Design1

1.2　The Role of Probability4

1.3 Sampling Procedures;Collection of Data7

1.4 Measures of Location:The Sample Mean9

1.5 Measures of Variability11

1.6　Discrete and Continuous Data14

1.7 Statistical Modeling,Scientific Inspection,and Graphical Diagnostics14

Preface15

Contents15

1.8 Graphical Methods and Data Description16

2.1 Sample Space22

2 Probability22

2.2 Events25

2.3 Counting Sample Points31

2.4　Probability of an Event39

2.5 Additive Rules43

2.6 Conditional Probability47

2.7 Multiplicative Rules50

2.8 Bayes'Rule57

Review Exercises61

3 Random Variables and Probability Distributions63

3.1 Concept of a Random Variable63

3.2　Discrete Probability Distributions65

3.3 Continuous Probability Distributions69

3.4 Joint Probability Distributions74

Review Exercises86

4　Mathematical Expectation88

4.1 Mean of a Random Variable88

4.2 Variance and Covariance95

4.3 Means and Variances of Linear Combinations of Random Variables103

4.4 Chebyshev's Theorem110

Review Exercises114

5 Some Discrete Probability Distributions115

5.1 Introduction115

5.2　Discrete Uniform Distribution116

5.3 Binomial and Multinomial Distributions117

5.4　Hypergeometric Distribution126

5.5 Negative Binomial and Geometric Distributions132

5.6　Poisson Distribution and the Poisson Process135

Review Exercises140

6 Some Continuous Probability Distributions142

6.1 Continuous Uniform Distribution142

6.2 Normal Distribution143

6.3 Areas Under the Normal Curve147

6.4 Applications of the Normal Distribution152

6.5 Normal Approximation to the Binomial158

6.6 Gamma and Exponential Distributions165

6.7 Applications of the Exponential and Gamma Distributions168

6.8 Chi-Squared Distribution170

6.9 Lognormal Distribution171

6.10 Weibull Distribution172

Review Exercises175

7 Functions of Random Variables（Optional）177

7.1 Introduction177

7.2 Transformations of Variables177

7.3 Moments and Moment-Generating Functions186

8 Fundamental Sampling Distributions and Data Descriptions194

8.1 Random Sampling194

8.2 Some Important Statistics197

8.3 Data Displays and Graphical Methods201

8.4 Sampling Distributions208

8.5 Sampling Distribution of Means209

8.6 Sampling Distribution of S2216

8.7 t-Distribution219

8.8 F-Distribution224

Review Exercises228

9 One-and Two-Sample Estimation Problems230

9.1 Introduction230

9.2 Statistical Inference230

9.3 Classical Methods of Estimation231

9.4 Single Sample:Estimating the Mean234

9.5 Standard Error of a Point Estimate240

9.6 Prediction Interval241

9.7 Tolerance Limits243

9.8 Two Samples:Estimating the Difference Between Two Means246

9.9 Paired Observations253

9.10 Single Sample:Estimating a Proportion257

9.11 Two Samples:Estimating the Difference Between Two Proportions261

9.12 Single Sample:Estimating the Variance264

9.13 Two Samples:Estimating the Ratio of Two Variances265

9.14 Bayesian Methods of Estimation（Optional）268

9.15 Maximum Likelihood Estimation（Optional）275

Review Exercises281

10.1 Statistical Hypotheses:General Concepts284

10 One-and Two-Sample Tests of Hypotheses284

10.2 Testing a Statistical Hypothesis286

10.3 One-and Two-Tailed Tests294

10.4 The Use of P-Values for Decision Making295

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

10.6 Relationship to Confidence Interval Estimation303

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

10.8 Two Samples:Tests on Two Means307

10.9 Choice of Sample Size for Testing Means312

10.10 Graphical Methods for Comparing Means316

10.11 One Sample:Test on a Single Proportion323

10.12 Two Samples:Tests on Two Proportions326

10.13 One-and Two-Sample Tests Concerning Variances328

10.14 Goodness-of-Fit Test333

10.15 Test for Independence（Categorical Data）336

10.16 Test for Homogeneity339

10.17 Testing for Several Proportions340

10.18 Two-Sample Case Study342

Review Exercises347

11 Simple Linear Regression and Correlation350

11.1 Introduction to Linear Regression350

11.2 Simple Linear Regression351

11.3 Least Squares and The Fitted Model355

11.4 Properties of the Least Squares Estimators360

11.5 Inferences Concerning the Regression Coefficients363

11.6 Prediction368

11.7 Choice of a Regression Model372

11.8 Analysis-of-Variance Approach373

11.9 Test for Linearity of Regression:Data with Repeated Observations375

11.10 Data Plots and Transformations383

11.11 Simple Linear Regression Case Study387

11.12 Correlation390

Review Exercises396

12 Multiple Linear Regression and Certain Nonlinear Regression Models400

12.1 Introduction400

12.2 Estimating the Coefficients401

12.3 Linear Regression Model Using Matrices（Optional）404

12.4 Properties of the Least Squares Estimators411

12.5 Inferences in Multiple Linear Regression413

12.6 Choice of a Fitted Model Through Hypothesis Testing420

12.7 Special Case of Orthogonality（Optional）423

12.8 Categorical or Indicator Variables427

12.9 Sequential Methods for Model Selection432

12.10 Study of Residuals and Violation of Assumptions438

12.11 Cross Validation,Cp,and Other Criteria for Model Selection442

12.12 Special Nonlinear Models for Nonideal Conditions452

Review Exercises456

13.1 Analysis-of-Variance Technique461

13 One-Factor Experiments:General461

13.2 The Strategy of Experimental Design463

13.3 One-Way Analysis of Variance:Completely Randomized Design463

13.4 Tests for the Equality of Several Variances469

13.5 Single-Degree-of-Freedom Comparisons473

13.6 Multiple Comparisons477

13.7 Comparing Treatments with a Control481

13.8 Comparing a Set of Treatments in Blocks486

13.9 Randomized Complete Block Designs487

13.10 Graphical Methods and Further Diagnostics494

13.11 Latin Squares（Optional）496

13.12 Random Effects Models502

13.13 Power of Analysis-of-Variance Tests507

13.14 Case Study511

Review Exercises515

14 Factorial Experiments（Two or More Factors）519

14.1 Introduction519

14.2 Interaction and the Two-Factor Experiment521

14.3 Two-Factor Analysis of Variance522

14.4 Graphical Analysis in the Two-Factor Problem530

14.5 Three-Factor Experiments535

14.6 Model Ⅱ and Ⅲ Factorial Experiments545

14.7 Choice of Sample Size549

Review Exercises552

15.1 Introduction555

15 2k Factorial Experiments and Fractions555

15.2 Analysis of Variance and the Calculation of Effects556

15.3 Nonreplicated 2k Factorial Experiment560

15.4 Injection Molding Case Study561

15.5 Factorial Experiments in Incomplete Blocks567

15.6 Partial Confounding572

15.7 Factorial Experiments in a Regression Setting575

15.8 The Orthogonal Design579

15.9 Fractional Factorial Experiments582

15.10 Analysis of Fractional Factorial Experiments585

15.11 Higher Fractions and Screening Designs589

15.12 Construction of Resolution Ⅲ and Ⅳ Designs with 8,16,and 32 Design Points590

15.13　Other Two-Level Resolution Ⅲ Designs;The Plackett-Burman Designs591

15.14　Taguchi's Robust Parameter Design592

Review Exercises598

16　Nonparametric Statistics600

16.1 Nonparametric Tests600

16.2 Sign Test601

16.3 Signed-Rank Test605

16.4 Rank-Sum Test610

16.5 Kruskal-Wallis Test613

16.6 Runs Test616

16.7 Tolerance Limits619

16.8 Rank Correlation Coefficient620

Review Exercises624

17 Statistical Quality Control625

17.1 Introduction625

17.2 Nature of the Control Limits627

17.3 Purposes of the Control Chart627

17.4 Control Charts for Variables628

17.5 Control Charts for Attributes643

17.6 Cusum Control Charts649

Review Exercises653

Bibliography656

Appendix:Statistical Tables and Proofs659

Answers to Odd-Numbered Exercises715

Index726