An Introduction to Probability and Statistical Inference, Second Edition

✍ Scribed by George G. Roussas

• Publisher: Academic Press
• Year: 2014
• Tongue: English
• Leaves: 609
• Edition: 2
• Category: Library

✦ Synopsis

Probability models, statistical methods, and the information to be gained from them is vital for work in business, engineering, sciences (including social and behavioral), and other fields. Data must be properly collected, analyzed and interpreted in order for the results to be used with confidence.

Award-winning author George Roussas introduces readers with no prior knowledge in probability or statistics to a thinking process to guide them toward the best solution to a posed question or situation. An Introduction to Probability and Statistical Inference provides a plethora of examples for each topic discussed, giving the reader more experience in applying statistical methods to different situations.

• Content, examples, an enhanced number of exercises, and graphical illustrations where appropriate to motivate the reader and demonstrate the applicability of probability and statistical inference in a great variety of human activities
• Reorganized material in the statistical portion of the book to ensure continuity and enhance understanding
• A relatively rigorous, yet accessible and always within the prescribed prerequisites, mathematical discussion of probability theory and statistical inference important to students in a broad variety of disciplines
• Relevant proofs where appropriate in each section, followed by exercises with useful clues to their solutions
• Brief answers to even-numbered exercises at the back of the book and detailed solutions to all exercises available to instructors in an Answers Manual

✦ Table of Contents

Content:
Inside Front Matter, Pages ES2-ES3
Front Matter, Pages i-ii
Copyright, Page iv
Dedication, Page v
Preface, Pages xi-xiv
Chapter 1 - Some motivating examples and some fundamental concepts, Pages 1-22
Chapter 2 - The concept of probability and basic results, Pages 23-76
Chapter 3 - Numerical characteristics of a random variable, some special random variables, Pages 77-133
Chapter 4 - Joint and conditional p.d.f.’s, conditional expectation and variance, moment generating function, covariance, and correlation coefficient, Pages 135-186
Chapter 5 - Independence of random variables and some applications, Pages 187-206
Chapter 6 - Transformation of random variables, Pages 207-243
Chapter 7 - Some modes of convergence of random variables, applications, Pages 245-271
Chapter 8 - An overview of statistical inference, Pages 273-285
Chapter 9 - Point estimation, Pages 287-328
Chapter 10 - Confidence intervals and confidence regions, Pages 329-347
Chapter 11 - Testing hypotheses, Pages 349-395
Chapter 12 - More about testing hypotheses, Pages 397-418
Chapter 13 - A simple linear regression model, Pages 419-452
Chapter 14 - Two models of analysis of variance, Pages 453-484
Chapter 15 - Some topics in nonparametric inference, Pages 485-515
Tables, Pages 517-550
Some notation and abbreviations, Pages 551-553
Answers to even-numbered exercises, Pages 555-598
Index, Pages 599-606
Inside Back Matter, Page ES4