Models for Probability and Statistical Inference

This book PDF is perfect for those who love Mathematics genre, written by James H. Stapleton and published by John Wiley & Sons which was released on 14 December 2007 with total hardcover pages 512. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Models for Probability and Statistical Inference books below.

Models for Probability and Statistical Inference
Author : James H. Stapleton
File Size : 55,7 Mb
Publisher : John Wiley & Sons
Language : English
Release Date : 14 December 2007
ISBN : 0470183403
Pages : 512 pages
Get Book

Models for Probability and Statistical Inference by James H. Stapleton Book PDF Summary

This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readers Models for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping. Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses modes of convergence of sequences of random variables, with special attention to convergence in distribution. The second half of the book addresses statistical inference, beginning with a discussion on point estimation and followed by coverage of consistency and confidence intervals. Further areas of exploration include: distributions defined in terms of the multivariate normal, chi-square, t, and F (central and non-central); the one- and two-sample Wilcoxon test, together with methods of estimation based on both; linear models with a linear space-projection approach; and logistic regression. Each section contains a set of problems ranging in difficulty from simple to more complex, and selected answers as well as proofs to almost all statements are provided. An abundant amount of figures in addition to helpful simulations and graphs produced by the statistical package S-Plus(r) are included to help build the intuition of readers.

Models for Probability and Statistical Inference

This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readers Models for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the

Get Book
Probability and Statistical Inference

Probability and Statistical Inference: From Basic Principles to Advanced Models covers aspects of probability, distribution theory, and inference that are fundamental to a proper understanding of data analysis and statistical modelling. It presents these topics in an accessible manner without sacrificing mathematical rigour, bridging the gap between the many excellent

Get Book
Probability and Statistical Inference

A carefully written text, suitable as an introductory course for second or third year students. The main scope of the text guides students towards a critical understanding and handling of data sets together with the ensuing testing of hypotheses. This approach distinguishes it from many other texts using statistical decision

Get Book
Probability Theory and Statistical Inference

This empirical research methods course enables informed implementation of statistical procedures, giving rise to trustworthy evidence.

Get Book
Probability and Statistical Inference

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

Get Book
Probability and Statistical Inference

This book is in two volumes, and is intended as a text for introductory courses in probability and statistics at the second or third year university level. It em phasizes applications and logical principles rather than mathematical theory. A good background in freshman calculus is sufficient for most of the

Get Book
Modelling  Inference and Data Analysis

Modelling, Inference and Data Analysis brings together key topics in mathematical statistics and presents them in a rigorous yet accessible manner. It covers aspects of probability, distribution theory and random processes that are fundamental to a proper understanding of inference. The book also discusses the properties of estimators constructed from

Get Book
An Introduction to Probability and Statistical Inference

An Introduction to Probability and Statistical Inference, Second Edition, guides you through probability models and statistical methods and helps you to think critically about various concepts. Written by award-winning author George Roussas, this book introduces readers with no prior knowledge in probability or statistics to a thinking process to help

Get Book