An Introduction to Statistical Inference and Its Applications with R / Edition 1

by Michael W. Trosset

Overview

Emphasizing concepts rather than recipes, An Introduction to Statistical Inference and Its Applications with R provides a clear exposition of the methods of statistical inference for students who are comfortable with mathematical notation. Numerous examples, case studies, and exercises are included. R is used to simplify computation, create figures, and draw pseudorandom samples—not to perform entire analyses.

After discussing the importance of chance in experimentation, the text develops basic tools of probability. The plug-in principle then provides a transition from populations to samples, motivating a variety of summary statistics and diagnostic techniques. The heart of the text is a careful exposition of point estimation, hypothesis testing, and confidence intervals. The author then explains procedures for 1- and 2-sample location problems, analysis of variance, goodness-of-fit, and correlation and regression. He concludes by discussing the role of simulation in modern statistical inference.

Focusing on the assumptions that underlie popular statistical methods, this textbook explains how and why these methods are used to analyze experimental data.

Product Details

ISBN-13:	9781584889472
Publisher:	Taylor & Francis
Publication date:	06/23/2009
Series:	Chapman & Hall/CRC Texts in Statistical Science , #81
Edition description:	New Edition
Pages:	496
Product dimensions:	6.40(w) x 9.40(h) x 1.20(d)

About the Author

Michael W. Trosset is Professor of Statistics and Director of the Indiana Statistical Consulting Center at Indiana University.

Table of Contents

Experiments. Mathematical Preliminaries. Probability. Discrete Random Variables. Continuous Random Variables. Quantifying Population Attributes. Data. Lots of Data. Inference. 1-Sample Location Problems. 2-Sample Location Problems. The Analysis of Variance. Goodness-of-Fit. Association. Simple Linear Regression. Simulation-Based Inference. R: A Statistical Programming Language. Index.