1st Edition
An Introduction to Statistical Inference and Its Applications with R
By Michael W. Trosset
Copyright 2009
496 Pages
72 B/W Illustrations
by
Chapman & Hall
496 Pages
72 B/W Illustrations
by
Chapman & Hall
496 Pages
by
Chapman & Hall
Also available as eBook on:
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... Read more
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.
Biography
Michael W. Trosset is Professor of Statistics and Director of the Indiana Statistical Consulting Center at Indiana University.
