Probability and Statistical Inference (Wiley Series in Probability and Statistics)

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.

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.

"Probability and Statistical Inference, Second Edition introduces key probability and statistical concepts through non-trivial, real-world examples and promotes the development of intuition rather than simple application. With its coverage of the recent advancements in computer-intensive methods, this update successfully provides the comprehensive tools needed to develop a broad understanding of the theory of statistics and its probabilistic foundations. This outstanding new edition continues to encourage readers to recognize and fully understand the why, not just the how, behind the concepts, theorems, and methods of statistics. Clear explanations are presented and applied to various examples that help to impart a deeper understanding of theorems and methods - from fundamental statistical concepts to computational details."--Jacket Experiments, Sample Spaces, and Events Probability Counting Conditional Probability; Independence Markov Chains* Random Variables: Univariate Case Random Variables: Multivariate Case Expectation Selected Families of Distributions Random Samples Introduction to Statistical Inference Estimation Testing Statistical Hypotheses Linear Models Rank Methods Analysis of Categorical Data Statistical Tables Answers to odd numbered problems. A book that stresses the comprehension of concepts instead of the simple acquisition of a skill or tool. It provides a mathematical framework that permits students to carry out various procedures using any number of computer software packages as opposed to relying on one particular package. It may be said that the primary purpose of using statistical methods is to help in making better decisions under conditions of uncertainty.