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An Introduction to Probability and Statistics

Online Resource
744 Seiten
2011 | 2nd edition
Wiley-Interscience (Hersteller)
978-1-118-16567-6 (ISBN)
CHF 298,65 inkl. MwSt
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The second edition of a well-received book that was published 24 years ago and continues to sell to this day, An Introduction to Probability and Statistics is now revised to incorporate new information as well as substantial updates of existing material.

Vijay K. Rohatgi, PhD, is Professor Emeritus in the Department of Mathematics and Statistics at Bowling Green State University. An Investment Research Consultant for PRI Investments, he is also the author of several books and over 100 research papers. A. K. Md. Ehsanes Saleh, PhD, is Distinguished Research Professor in the School of Mathematics and Statistics at Carleton University. Dr. Saleh is the author of more than 200 journal articles, and his research interests include nonparametric statistics, order statistics, and robust estimation.

Preface to the Second Edition xi

Preface to the First Edition xiii

1. Probability 1

1.1 Introduction 1

1.2 Sample Space 2

1.3 Probability Axioms 7

1.4 Combinatorics: Probability on Finite Sample Spaces 21

1.5 Conditional Probability and Bayes Theorem 28

1.6 Independence of Events 33

2. Random Variables and Their Probability Distributions 40

2.1 Introduction 40

2.2 Random Variables 40

2.3 Probability Distribution of a Random Variable 43

2.4 Discrete and Continuous Random Variables 48

2.5 Functions of a Random Variable 57

3. Moments and Generating Functions 69

3.1 Introduction 69

3.2 Moments of a Distribution Function 69

3.3 Generating Functions 85

3.4 Some Moment Inequalities 95

4. Multiple Random Variables 102

4.1 Introduction 102

4.2 Multiple Random Variables 102

4.3 Independent Random Variables 119

4.4 Functions of Several Random Variables 127

4.5 Covariance Correlation and Moments 149

4.6 Conditional Expectation 164

4.7 Order Statistics and Their Distributions 171

5. Some Special Distributions 180

5.1 Introduction 180

5.2 Some Discrete Distributions 180

5.3 Some Continuous Distributions 204

5.4 Bivariate and Multivariate Normal Distributions 238

5.5 Exponential Family of Distributions 251

6. Limit Theorems 256

6.1 Introduction 256

6.2 Modes of Convergence 256

6.3 Weak Law of Large Numbers 274

6.4 Strong Law of Large Numbers 281

6.5 Limiting Moment Generating Functions 289

6.6 Central Limit Theorem 293

7. Sample Moments and Their Distributions 306

7.1 Introduction 306

7.2 Random Sampling 307

7.3 Sample Characteristics and Their Distributions 310

7.4 Chi-Square f- and F-Distributions: Exact Sampling Distributions 324

7.5 Large-Sample Theory 334

7.6 Distribution of (X S2) in Sampling from a Normal Population 339

7.7 Sampling from a Bivariate Normal Distribution 344

8. Parametric Point Estimation 353

8.1 Introduction 353

8.2 Problem of Point Estimation 354

8.3 Sufficiency Completeness and Ancillarity 358

8.4 Unbiased Estimation 377

8.5 Unbiased Estimation (Continued): Lower Bound for the Variance of an Estimator 391

8.6 Substitution Principle (Method of Moments) 406

8.7 Maximum Likelihood Estimators 409

8.8 Bayes and Minimax Estimation 424

8.9 Principle of Equivariance 442

9. Neyman-Pearson Theory of Testing of Hypotheses 454

9.1 Introduction 454

9.2 Some Fundamental Notions of Hypotheses Testing 454

9.3 Neyman-Pearson Lemma 464

9.4 Families with Monotone Likelihood Ratio 472

9.5 Unbiased and Invariant Tests 479

9.6 Locally Most Powerful Tests 486

10. Some Further Results of Hypothesis Testing 490

10.1 Introduction 490

10.2 Generalized Likelihood Ratio Tests 490

10.3 Chi-Square Tests 500

10.4 /-Tests 512

10.5 F-Tests 518

10.6 Bayes and Minimax Procedures 520

11. Confidence Estimation 527

11.1 Introduction 527

11.2 Some Fundamental Notions of Confidence Estimation 527

11.3 Methods of Finding Confidence Intervals 532

11.4 Shortest-Length Confidence Intervals 546

11.5 Unbiased and Equivariant Confidence Intervals 553

12. General Linear Hypothesis 561

12.1 Introduction 561

12.2 General Linear Hypothesis 561

12.3 Regression Model 569

12.4 One-Way Analysis of Variance 577

12.5 Two-Way Analysis of Variance with One Observation per Cell 583

12.6 Two-Way Analysis of Variance with Interaction 590

13. Nonparametric Statistical Inference 598

13.1 Introduction 598

13.2 U-Statistics 598

13.3 Some Single-Sample Problems 608

13.4 Some Two-Sample Problems 624

13.5 Tests of Independence 633

13.6 Some Applications of Order Statistics 644

13.7 Robustness 650

References 663

Frequently Used Symbols and Abbreviations 669

Statistical Tables 673

Answers to Selected Problems 693

Author Index 705

Subject Index 707

Erscheint lt. Verlag 19.9.2011
Reihe/Serie Wiley Series in Probability and Statistics
Sprache englisch
Themenwelt Mathematik / Informatik Mathematik Statistik
Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
ISBN-10 1-118-16567-5 / 1118165675
ISBN-13 978-1-118-16567-6 / 9781118165676
Zustand Neuware
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