Designed for a one-semester advanced undergraduate or graduate course, this text clearly explains the underlying ideas and principles of major statistical concepts, including parameter estimation, confidence intervals, hypothesis testing, asymptotic analysis, Bayesian inference, and elements of decision theory. It introduces these topics on a clear intuitive level using illustrative examples in addition to the formal definitions, theorems, and proofs. Requiring no heavy calculus, simple questions throughout the text help students check their understanding of the material.
Inhaltsverzeichnis
Introduction. Point Estimation. Confidence Intervals, Bounds, and Regions. Hypothesis Testing. Asymptotic Analysis. Bayesian Inference. Elements of Statistical Decision Theory. Linear Models. Appendices. Index.
