Description
Book SynopsisElliot A. Tanis: Tanis has written 30 articles in probability and statistics, many illustrating applications using the computer. He has authored or co-authored four books in probability and statistics. These include Probability & Statistics Explorations with MAPLE, 2nd edition, with Zaven Karian in 1999 and Probability and Statistical Inference, 7th edition, with Robert V. Hogg in 2006. He was Chairperson (1976-77) and Governor (1989-92) of the Michigan Section of the Mathematical Association of America. He was a winner of the Hope's Outstanding Professor Educator (H.O.P.E.) award in 1989 and received the award for Distinguished College or University Teaching of Mathematics, Michigan Section, MAA, in 1992. Tanis became Professor Emeritus of Mathematics at Hope College in 2000 after teaching there 35 years.
Robert V. Hogg: Hogg has written over 70 research articles and coauthored five books, including Introductio
Trade Review
"The authors have years of experience analyzing real data, have collected excellent examples to illustrate statistical concepts and anomalies, and are proven writers in the discipline." Professor Charles Sommer, SUNY College at Brockport "The authors have done a wonderful job in writing this book...I must congratulate them for doing a great job and helping in the development of the subject of Statistics." Professor M.L. Aggarwal, The University of Memphis
Table of Contents
Preface
1. Probability
1.1 Basic Concepts
1.2 Methods of Enumeration
1.3 Conditional Probability
1.4 Independent Events
1.5 Bayes's Theorem
Chapter One Comments
2. Discrete Distributions
2.1 Discrete Probability Distributions
2.2 Expectations
2.3 Special Discrete Distributions
2.4 Estimation
2.5 Linear Functions of Independent Random Variables
2.6 Multivariate Discrete Distributions
Chapter Two Comments
3. Continuous Distributions
3.1 Descriptive Statistics and EDA
3.2 Continuous Probability Distributions
3.3 Special Continuous Distributions
3.4 The Normal Distribution
3.5 Estimation in the Continuous Case
3.6 The Central Limit Theorem
3.7 Approximations for Discrete Distributions
Chapter Three Comemnts
4. Applications of Statistical Inference
4.1 Summary of Necessary Theoretical Results
4.2 Confidence Intervals Using X2 F,and T
4.3 Confidence Intervals and Tests of Hypotheses
4.4 Basic Tests Concerning One Parameter
4.5 Tests of the Equality of Two Parameters
4.6 Simple Linear Regression
4.7 More on Linear Regression
4.8 One-Factor Analysis of Variance
4.9 Distribution-Free Confidence and Tolerance Intervals
4.10 Chi-Square Goodness of Fit Tests
4.11 Contingency Tables
Chapter Four Comments
5. Computer Oriented Techniques
5.1 Computation of Statistics
5.2 Computer Algebra Systems
5.3 Simulation
5.4 Resampling
Chapter Five Comments
6. Some Sampling Distribution Theory
6.1 Moment-Generation Function Technique
6.2 M.G.F of Linear Functions
6.3 Limiting Moment-Generating Functions
6.4 Use of Order Statistics in Non-regular Cases
Chapter Six Comments
