Probability and Statistical Inference, Second Edition

✍ Scribed by Robert Bartoszy?ski, Magdalena Niewiadomska?Bugaj(auth.)

• Year: 2008
• Tongue: English
• Leaves: 655
• Category: Library

✦ Synopsis

Now updated in a valuable new edition—this user-friendly book focuses on understanding the "why" of mathematical statistics

Probability and Statistical Inference, Second Edition introduces key probability and statis-tical concepts through non-trivial, real-world examples and promotes the developmentof intuition rather than simple application. With its coverage of the recent advancements in computer-intensive methods, this update successfully provides the comp-rehensive tools needed to develop a broad understanding of the theory of statisticsand its probabilistic foundations. This outstanding new edition continues to encouragereaders to recognize and fully understand the why, not just the how, behind the concepts,theorems, and methods of statistics. Clear explanations are presented and appliedto various examples that help to impart a deeper understanding of theorems and methods—from fundamental statistical concepts to computational details.

Additional features of this Second Edition include:

• A new chapter on random samples

• Coverage of computer-intensive techniques in statistical inference featuring Monte Carlo and resampling methods, such as bootstrap and permutation tests, bootstrap confidence intervals with supporting R codes, and additional examples available via the book's FTP site

• Treatment of survival and hazard function, methods of obtaining estimators, and Bayes estimating

• Real-world examples that illuminate presented concepts

• Exercises at the end of each section

Providing a straightforward, contemporary approach to modern-day statistical applications, Probability and Statistical Inference, Second Edition is an ideal text for advanced undergraduate- and graduate-level courses in probability and statistical inference. It also serves as a valuable reference for practitioners in any discipline who wish to gain further insight into the latest statistical tools.Content:
Chapter 1 Experiments, Sample Spaces, and Events (pages 1–24):
Chapter 2 Probability (pages 25–45):
Chapter 3 Counting (pages 47–72):
Chapter 4 Conditional Probability; Independence (pages 73–102):
Chapter 5 Markov Chains (pages 103–124):
Chapter 6 Random Variables: Univariate Case (pages 125–160):
Chapter 7 Random Variables: Multivariate Case (pages 161–202):
Chapter 8 Expectation (pages 203–255):
Chapter 9 Selected Families of Distributions (pages 257–310):
Chapter 10 Random Samples (pages 311–350):
Chapter 11 Introduction to Statistical Inference (pages 351–371):
Chapter 12 Estimation (pages 373–454):
Chapter 13 Testing Statistical Hypotheses (pages 455–516):
Chapter 14 Linear Models (pages 517–558):
Chapter 15 Rank Methods (pages 559–583):
Chapter 16 Analysis of Categorical Data (pages 585–616):