An introduction to probability and mathematical statistics / Howard G. Tucker

Tucker, Howard G.

Published by New York ; London : Academic Press, 1962

About this Item

Near fine cloth copy in a good if slightly edge-torn and dust-dulled dust-wrapper, now mylar-sleeved. Remains particularly well-preserved overall; tight, bright, clean and strong. Physical description; 228 p. Notes; Includes bibliographical references and index. Contents; Front Cover; An Introduction to Probability and Mathematical Statistics; Copyright Page; Dedication; Preface; Table of Contents; Chapter 1. Events and Probabilities; 1.1 Combinatorial Probability; 1.2 The Fundamental Probability Set and the Algebra of Events; 1.3 The Axioms of a Probability Space; Chapter 2. Dependent and Independent Events; 2.1 Conditional Probability; 2.2 Stochastic Independence; 2.3 An Application in Physics of the Notion of Independence; Chapter 3. Random Variables and Probability Distributions; 3.1 The Definition of a Function; 3.2 The Definition of a Random Variable 3.3 Combinations of Random Variables3.4 Distribution Functions; 3.5 Multivariate Distribution Functions; Chapter 4. Discrete Distributions; 4.1 Univariate Discrete Distributions; 4.2 The Binomial and Pascal Distributions; 4.3 The Hypergeometric Distribution; 4.4 The Poisson Distribution; 4.5 Multivariate Discrete Densities; Chapter 5. Absolutely Continuous Distributions; 5.1 Absolutely Continuous Distributions; 5.2 Densities of Functions of Random Variables; Chapter 6. Some Special Absolutely Continuous Distributions; 6.1 The Gamma and Beta Functions; 6.2 The Normal Distribution 6.3 The Negative Exponential Distribution6.4 The Chi-Square Distribution; 6.5 The F-Distribution and the t-Distribution; Chapter 7. Expectation and Limit Theorems; 7.1 Definition of Expectation; 7.2 Expectation of Functions of Random Variables; 7.3 Moments and Central Moments; 7.4 Convergence in Probability; 7.5 Limit Theorems; Chapter 8. Point Estimation; 8.1 Sampling; 8.2 Unbiased and Consistent Estimates; 8.3 The Method of Moments; 8.4 Minimum Variance Estimates; 8.5 The Principle of Maximum Likelihood; Chapter 9. Notes on Matrix Theory; Chapter 10. The Multivariate Normal Distribution 10.1 The Multivariate Normal Density10.2 Properties of the Multivariate Normal Distribution; 10.3 Cochran's Theorem; 10.4 Proof of the Independence of the Sample Mean and Sample Variance for a Normal Population; Chapter 11. Testing Statistical Hypotheses: Simple Hypothesis vs. Simple Alternative; 11.1 Fundamental Notions of Hypothesis Testing; 11.2 Simple Hypothesis vs. Simple Alternative; 11.3 The Neyman-Pearson Fundamental Lemma; 11.4 Randomized Tests; Chapter 12. Testing Simple and Composite Hypotheses; 12.1 Uniformly Most Powerful Critical Regions; 12.2 The Likelihood Ratio Test 12.3 The t-Test12.4 The Analysis of Variance; Chapter 13. Confidence Intervals; 13.1 The Neyman Theory of Confidence Intervals; 13.2 The Relation between Confidence Intervals and Tests of Hypotheses; 13.3 Necessary and Sufficient Conditions for the Existence of Confidence Intervals; Suggested Reading; Tables I-IV; Index. Subject; Probabilities. Mathematical statistics. probability. applied mathematics. mathematics. 1 Kg.

Seller Inventory # 432890

Bibliographic Details

• Title: An introduction to probability and mathematical statistics / Howard G. Tucker
• Publisher: New York ; London : Academic Press
• Publication Date: 1962
• Binding: Hardcover
• Edition: First Edition.