Statistical Analysis and Data Display: An Intermediate Course with Examples in S-Plus, R, and SAS / Edition 1

Statistical Analysis and Data Display: An Intermediate Course with Examples in S-Plus, R, and SAS / Edition 1

by Richard M. Heiberger, Burt Holland
     
 

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ISBN-10: 1441923209

ISBN-13: 9781441923202

Pub. Date: 11/19/2010

Publisher: Springer New York

This presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, graphics, and accompanying computer listings. They emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how tabular

Overview

This presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, graphics, and accompanying computer listings. They emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how tabular results are used to confirm the visual impressions derived from the graphs. Many of the graphical formats are novel and appear here for the first time in print.

Product Details

ISBN-13:
9781441923202
Publisher:
Springer New York
Publication date:
11/19/2010
Series:
Springer Texts in Statistics Series
Edition description:
Softcover reprint of hardcover 1st ed. 2004
Pages:
730
Product dimensions:
7.00(w) x 9.90(h) x 1.50(d)

Table of Contents

Introduction and Motivation.- Data and Statistics.- Statistics Concepts.- Graphs.- Introductory Inference.- One-Way Analysis of Variance, ANOVA.- Multiple Comparisons.- Linear Regression by Least Squares.- Multiple Regression - More Than One Predictor.- Multiple Regression - Dummy Variables and Contrasts.- Multiple Regression - Regression Diagnostics.- Two-Way Analysis of Variance.- Design of Experiments - Factorial Designs.- Design of Experiments - More Complex Designs.- Bivariate Statistics - Discrete Data.- Nonparametrics.- Logistic Regression.- Time Series Analysis.

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