Brief Course in Mathematical Statistics, A
Will be published approx. on 23. January 2007
Book
Paperback/Softback
368 pages
978-0-13-175139-2 (ISBN)
Description
For a one-semester course in Mathematical Statistics. This innovative new introduction to Mathematical Statistics covers the important concept of estimation at a point much earlier than other texts (Chapter 2). Thought-provoking pedagogical aids help students test their understanding and relate concepts to everyday life. Ideal for courses that offer a little less probability than usual, this book requires one year of calculus as a prerequisite.
Reviews / Votes
"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 MemphisMore details
Persons
Elliot 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 "Introduction of Mathematical Statistics," 6th edition, with J. W. McKean and A.T. Craig, and "Probability and Statistical Inference," 7th edition, with E.A. Tanis. He was President of the American Statistical Association in 1988 and was given the Founders and Noether awards of that society. Earlier he received an Outstanding Teacher award of the Mathematical Association of America and, in 2007, will receive the Carver Medal from the Institute of Mathematical Statistics. Hogg became Professor Emeritus of Statistics at the University of Iowa in 2001 after teaching there 51 years.
Robert V. Hogg: Hogg has written over 70 research articles and coauthored five books, including "Introduction of Mathematical Statistics," 6th edition, with J. W. McKean and A.T. Craig, and "Probability and Statistical Inference," 7th edition, with E.A. Tanis. He was President of the American Statistical Association in 1988 and was given the Founders and Noether awards of that society. Earlier he received an Outstanding Teacher award of the Mathematical Association of America and, in 2007, will receive the Carver Medal from the Institute of Mathematical Statistics. Hogg became Professor Emeritus of Statistics at the University of Iowa in 2001 after teaching there 51 years.
Content
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
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