Mathematical Statistics (1版)

Mathematical Statistics describes the mathematical underpinnings associated with the practice of statistics. The pre-requisite for this book is a calculus-based course in probability. Nearly 200 figures and dozens of Monte Carlo simulation experiments in R help develop the intuition behind the statistical methods. Real-world problems from a wide range of fields help the reader apply the statistical methods. Over 300 exercises are used to reinforce concepts and make this book appropriate for classroom use.

Preface Random Sampling: Statistical Graphics Random Sampling, Statistics, and Sampling Distributions Estimating Central Tendency Estimating Dispersion Sampling from Normal Populations Exercises Point Estimation: Introduction Method of Moments Maximum Likelihood Estimation Properties of Point Estimators Exercises Interval Estimation: Exact Confidence Intervals Approximate Confidence Intervals Asymptotically Exact Confidence Intervals Other Interval Estimators Exercises Hypothesis Testing: Elements of Hypothesis Testing Significance Tests Sampling from Normal Populations Sample Size Determination Confidence Intervals, Hypothesis Tests, & Significance Tests Most Powerful Tests Likelihood Ratio Tests Exercises Index