Probability œ [and] statistics

I found it a lucid and useful text. Could recommend it for an applied mathematician or physicist wanting to brush up on statistics. Preface......Page 10 PART ONE:PROBABILITY......Page 12 1-1 Introduction......Page 14 1-2 The Four Interpretations of Probability......Page 20 2-1 Set Theory......Page 30 2-2 Probability Space......Page 40 2-3 Conditional Probability and Independence......Page 56 Problems......Page 67 3-1 Dual Meaning of Repeated Trials......Page 70 3-2 Bernoulli Trials......Page 75 3-3 Asymptotic Theorems......Page 81 3-4 Rare Events and Poisson Points......Page 88 Problems......Page 92 4-1 Introduction......Page 95 4-2 The Distribution Function......Page 99 4-3 Illustrations......Page 112 4-4 Functions of One Random Variable......Page 123 4-5 Mean and Variance......Page 132 Problems......Page 142 5-1 The Joint Distribution Function......Page 146 5-2 Mean, Correlation, Moments......Page 155 5-3 Functions of Two Random Variables......Page 166 Problems......Page 176 6-1 Conditional Distributions......Page 179 6-2 Bayes' Formulas......Page 185 6-3 Nonlinear Regression and Prediction......Page 192 6-4 System Reliability......Page 197 Problems......Page 206 7-1 General Concepts......Page 208 7-2 Applications......Page 215 7-3 Central Limit Theorem......Page 225 7-4 Special Distributions of Statistics......Page 230 Appendix: Chi-Square Quadratic Forms......Page 237 Problems......Page 240 PART TWO:STATISTICS......Page 244 8-1 Introduction......Page 246 8-2 The Major Areas of Statistics......Page 249 8-3 Random Numbers and Computer Simulation......Page 262 9-1 General Concepts......Page 284 9-2 Expected Values......Page 286 9-3 Variance and Correlation......Page 304 9-4 Percentiles and Distributions......Page 308 9-5 Moments and Maximum Likelihood......Page 312 9-6 Best Estimators and the Rao-Cramer Bound......Page 318 Problems......Page 327 10-1 General Concepts......Page 332 10-2 Basic Applications......Page 335 10-3 Quality Control......Page 353 10-4 Goodness-of-Fit Testing......Page 359 10-5 Analysis of Variance......Page 371 10-6 Neyman-Pearson, Sequential, and Likelihood Ratio Tests......Page 380 Problems......Page 393 11-1 Introduction......Page 399 11-2 Deterministic Interpretation......Page 402 11-3 Statistical Interpretation......Page 413 11-4 Prediction......Page 418 Problems......Page 422 12-1 Entropy of Partitions and Random Variables......Page 425 12-2 Maximum Entropy and Statistics......Page 433 12-3 Typical Sequences and Relative Frequency......Page 441 Problems......Page 446 Tables......Page 448 Answers and Hints for Selected Problems......Page 454 Index......Page 459

A developed, complete treatment of undergraduate probability and statistics by a very well known author. The approach develops a unified theory presented with clarity and economy. Included many examples and applications. Appropriate for an introductory undergraduate course in probability and statistics for students in engineering, math, the physical sciences, and computer science.(vs. Walpole/Myers, Miller/Freund, Devore, Scheaffer/McClave, Milton/Arnold)

Confronts the conceptual difficulty many students have in learning probability and statistics by developing a precise foundation in concepts, working through theory, and then illustrating each concept with examples and applications directly related to the theory.