The purpose of the third edition of this book is to give a sound and self-contained (in the sense that the necessary probability theory is included) Introduction to classical or mainstream statistical theory.
Key Features:
The book is designed to be used in either the quarter system or the semester system. In a quarter system, Chaps. I through V could be covered in the first quarter, Chaps. VI through Part of VIII the second quarter, and the rest of the book the third quarter. In a semester system, Chaps. I through VI could be covered the first semester and the remaining chapters the second semester.
Several sections or subsections can be omitted without disruptiing the continuity of presentation.
The many problems are intended to be essential for learning the material in the book. Some of the more difficult problems have been starred.
About the Author:
Alexander Mood
ALEXANDER M. MOOD
professor of Administration and
Director of public policy Research Organization
University of California,Irvine
Franklin Graybill
FRANKLIN A> GRAYBILL
Department of statistics
Colorado site University
fort collins, colorado
Duane Boes
DUANE C.BOES
Department of statistics
colorado state University
Fort Collins, colorado
Table of Content:
Preface to the Third Edition
Excerpts from the First and Second Edition Prefaces
PART I: PROBABILITY
Chapter 1. Introduction and Summary
Chapter 2. Kinds of Probability
Chapter 3. Probability-Axiomatic
PART II: RANDOM VARIABLES, DISTRIBUTION FUNCTIONS, AND EXPECTATION
Chapter 1. Introduction and Summary
Chapter 2. Random Variable and Cumulative Distribution Function
Chapter 3. Density Functions
Chapter 4. Expectations and Moments
PART III: SPECIAL PARAMETRIC FAMILITES OF UNIVARIATE DISTRIBUTIONS
Chapter 1. Introduction and Summary
Chapter 2. Discrete Distributions
Chapter 3. Continuous Distributions
Chapter 4. Comments
PART IV. JOINT AND CONDITIONAL DISTRIBUTIONS, STOCHASTIC INDEPENDENCE,MORE EXCEPTION
Chapter 1. Introduction and Summary
Chapter 2. Joint Distibution Functions
Chapter 3. Conditional Distributions and Stochastic Independence
Chapter 4. Expectation
Chapter 5. Bivariate Normal Distribution
PART V: DISTRIBUTIONS OF FUNCTIONS AND RANDOM VARIABLES
Chapter 1. Introduction and Summary
Chapter 2. Expectations of Functions of Random Variables
Chatper 3. Cumulative-Distribution-Function Technique
Chapter 4. Moment-Generating-Function Technique
Chapter 5. The Transformation Y=g(x)
Chapter 6. Transformations
PART VI: SAMPLING AND SAMPLING DISTRIBUTIONS
Chapter 1. Introduction and Summary
Chapter 2. Sampling
Chapter 3. Sample Mean
Chapter 4. Sampling from the Normal Distributions
Chapter 5. Order Statistics
PART VII: PARAMETRIC POINT ESTIMATION
Chapter 1. Introduction and Summary
Chapter 2. Methods of Finding Estimators
Chapter 3. Properties of Point Estimators
Chapter 4. Sufficiency
Chapter 5. Unbiased Estimation
Chapter 6. Location or Scale Invariance
Chapter 7. Bayes Estimators
Chapter 8. Vector of Parameters
Chapter 9. Optimum Properties of Maximum-likelihood Estimation
PART VIII: Parametric Interval Estimation
Chapter 1. Introduction and Summary
Chapter 2. Confidence Intervals
Chapter 3. Sampling from the Normal Distribution
Chapter 4. Methods of Finding Confidence Intervals
Chapter 5. Large-Sample Confidence Intervals
Chapter 6. Bayesian Interval Estimates
PART IX: TESTS OF HYPOTHESES
Chapter 1. Introduction and Summary
Chapter 2. Simple Hypothesis versus Simple Alternative
Chapter 3. Composite Hypotheses
Chapter 4. Tests of Hypotheses-Sampling from the National Distribution
Chapter 5. Chi-Square Tests
Chapter 6. Tests of Hypotheses and Confidence Intervals
Chapter 7. Sequential Tests of Hypotheses
PART X: LINEAR MODELS
Chapter 1. Introduction and Summary
Chapter 2. Examples of the Linear Model
Chapter 3. Definition of Linear Model
Chapter 4. Point Estimation-Case A
Chapter 5. Confidence Intervals-Case A
Chapter 6. Tests of Hypotheses-Case A
Chapter 7. Point Estimation-Case B
PART XI: NONPARAMETRIC METHOD
Chapter 1. Introduction and Summary
Chapter 2. Inferences Concerning a Cumulative Distribution Function
Chapter 3. Inferences Concerning Quantiles
Chapter 4. Tolerance Limits
Chapter 5. Equality of Two Distributions
APPENDIX A. MATHEMATICAL ADDENDUM
chapter 1. Introduction
Chapter 2. Noncalculus
Chapter 3. Calculus
APPENDIX B. TABULAR SUMMARY OF PARAMETRIC FAMILIES OF DISTRIBUTIONS
chapter 1. Introduction
APPENDIX C. REFERENCES AND RELATED READING
APPENDIX D. TABLES
chapter 1. Discription of Tables
Index
