工程师和科学家实用统计分析 基于计算机的方法 英文版PDF|Epub|txt|kindle电子书版本网盘下载

工程师和科学家实用统计分析 基于计算机的方法 英文版PDF格式电子书版下载

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1 Introduction1

2 Probability:Fundamental Concepts and Operational Rules4

2.1 Repeatable Experiments and Sample Spaces5

2.2 Events and the Venn Diagram6

2.3 Probability and Operational Rules9

2.4 Conditional Probability and Statistical Independence13

List of Figures15

CONTENTS15

2.5 Bayes'Formula16

2.6 Counting Techniques:Trees,Combinations,and Permutations17

6.1 Introduction18

List of Tables19

Preface23

Exercises23

Computer-Based Exercises27

3 Discrete Random Variables28

3.1 Random Variables and General Properties of Probability Distributions29

3.2 The Binomial Distribution34

3.3 Some Popular Discrete Distributions and Their Relationships39

3.4 A Suggestion for Solving Problems Involving Discrete Random Variables50

3.5 Discrete Bivariate Probability Distribution Functions50

Exercises55

Computer-Based Exercises60

4 Continuous Random Variables62

4.1 General Properties of Continuous Random Variables63

4.2 The Normal Distribution65

4.3 Some Popular Continuous Distributions and Their Relationships70

4.4 Continuous Bivariate Probability Density Functions82

Exercises86

Computer-Based Exercises91

5 The Mean,Variance,Expected Value Operator,and Other Functions of Random Variables93

5.1 Introduction94

5.2 Measures of Centrality:The Mean,Median,and Mode94

5.3 Measures of Variability:The Range and the Variance98

5.4 The Expected Value Operator100

5.5 Two Additional Measures of a Probability Distribution Function:Skewness and Kurtosis101

5.6 The Covariance and Correlation of Bivariate Distribution Functions107

5.7 Functions of One or More Random Variables109

5.8 A Comment about the"Road Ahead"113

Exercises113

6 Classification and Description of Sample Data118

6.2 The Frequency Table and Its Outgrowths119

6.3 Graphical Presentations of the Frequency Table122

6.4 Sample Estimates126

6.5 Some Suggestions for Further Study129

Exercises130

7 Sampling Distributions:Random Sampling,the Sample Mean and Sample Variance,and the Central Limit Theorem137

7.1 Random Sampling from Finite and Infinite Populations138

7.2 The Distribution of the Sample Mean,？142

7.3 The Distribution of the Sample Variance,S2149

Exercises151

8 Point and Interval Estimators and the Estimation of the Mean and the Variance154

8.1 Point Estimators155

8.2 Interval Estimators157

8.3 Interval Estimates for Population Means158

8.4 Determining an Adequate Sample Size for Interval Estimation of a Mean163

8.5 Confidence Intervals for the Variance163

8.6 Estimating Proportions164

8.7 The Three General Types of Confidence Intervals165

Exercises167

9 Hypothesis Tests about a Single Mean,a Single Proportion,or a Single Variance171

9.1 Introduction172

9.2 Hypothesis Tests about a Single Mean174

9.3 Hypothesis Tests about a Single Proportion186

9.4 Hypothesis Tests about a Single Variance188

9.5 Some Comments on the Difference between Statistical Significance and Practical Significance191

Exercises192

10 Hypothesis Tests for Two Means,Two Variances,or Two Proportions195

10.1 Tests Comparing Two Means When σ1 and σ2 Are Known196

10.2 Tests Comparing Two Means When σ1 and σ2 Are Unknown199

10.3 Tests Comparing Two Means When the Data Are Paired201

10.4 Tests Concerning Two Variances202

10.5 Hypothesis Tests about Two Proportions204

Exercises207

11 Fitting Equations to Data,Part Ⅰ:Simple Linear Regression Analysis and Curvilinear Regression Analysis211

11.1 Introduction212

11.2 The Mathematical Model for Simple Linear Regression Analysis213

11.3 Obtaining the Best Estimates of β0 and β1215

11.4 The Multiple Correlation Coefficient Squared,r2218

11.5 A Hypothesis Test for the Significance of the Fitted Line220

11.6 The Construction of Confidence Intervals about β0,β1,the Mean of Y,and a Predicted Value of Y222

11.7 The Correlation Coefficient and a Joint Confidence Region for β0 and β1224

11.8 Graphical Methods of Investigating Data Structure in SLR227

11.9 The Study of Sample Residuals in SLR230

11.10 Curvilinear Regression235

Exercises240

12 Fitting Equations to Data,Part Ⅱ:Multivariate Regression Analysis245

12.1 Introduction246

12.2 Estimating the Parameter Values in MLR248

12.3 Some Useful Theoretical Properties of MLR250

12.4 The Variance-Covariance and Correlation Matrices of ？252

12.5 Univariate Confidence Intervals on the βi and on predicted values of y253

12.6 Determining Whether a Fit is Adequate and Comparing Competing Models255

Exercises259

12.7 The General Linear Model and"the Other Side of the Coin"259

13 Hypothesis Tests for Two or More Means:Analysis of Variance-Single-Factor Designs265

13.1 Introduction266

13.2 Completely Randomized Single-Factor Experiments266

13.3 How to Determine Which Means Differ When H0 Is Rejected271

13 4 The Operating Characteristic Curve for the Completely Randomized Single-Factor Design275

13.5 The Randomized Block Design:A Single-Factor Design with One Restriction on Randomization280

13.6 Some Comments on Additional Single-Factor Designs and on Missing Data285

Exercises286

14 Factorial Analysis of Variance293

14.1 Introduction293

14.2 A Two-Factor Factorial ANOVA Design294

14.3 Higher-Order Multifactor Factorial Designs300

Exercises300

15 An Introduction to Statistical Quality Control303

15.2 A Control Chart for Variables:The？-R Chart304

15.1 Introduction304

15.3 Control Charts for Attributes314

15.4 Acceptance Sampling:Construction of Sampling Plans and Their Uses319

Exercises327

16 Some Additional Methods of Data Analysis332

16.1 Introduction333

16.2 The x2 Test for Goodness of Fit333

16.3 A Distribution-Free AIternative to the t Test:The Wilcoxon Signed Rank Test336

16.4 A Distribution-Free Alternative to the Two-Sample t Test:The Wilcoxon Rank Sum Test341

16.5 A Distribution-Free Alternative to the Completely Randomized Single-Factor ANOVA:The Kruskal-Wallis Test344

Exercises346

References and Suggested Readings349

Statistcal Tables351

Answers to Selected Exercises375

Index385