Statistical Analysis and Data Display: An Intermediate Course with Examples in R

This document was uploaded by one of our users. The uploader already confirmed that they had the permission to publish it. If you are author/publisher or own the copyright of this documents, please report to us by using this DMCA report form.

Simply click on the Download Book button.

Yes, Book downloads on Ebookily are 100% Free.

Sometimes the book is free on Amazon As well, so go ahead and hit "Search on Amazon"

This contemporary 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―for all the methods they cover. They emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how accompanying traditional tabular results are used to confirm the visual impressions derived directly from the graphs. Many of the graphical formats are novel and appear here for the first time in print. All chapters have exercises.

The second edition features new chapters, sections and revisions. New chapters cover Likert Scale Data to build on the importance of rating scales in fields from population studies to psychometrics.

This book can serve as a standalone text for statistics majors at the master's level and for other quantitatively oriented disciplines at the doctoral level, and as a reference book for researchers. In-depth discussions of regression analysis, analysis of variance, and design of experiments are followed by introductions to analysis of discrete bivariate data, nonparametrics, logistic regression, and ARIMA time series modeling. The authors illustrate classical concepts and techniques with a variety of case studies using both newer graphical tools and traditional tabular displays.

The authors provide and discuss R and SAS executable functions and macros for all new graphical display formats. All graphs and tabular output in the book were constructed using these programs. Complete transcripts for all examples and figures are provided for readers to use as models for their own analyses.

Author(s): Richard M. Heiberger, Burt Holland
Series: Springer Texts in Statistics
Edition: 2nd ed. 2015
Publisher: Springer
Year: 2015

Language: English
Pages: 898
Tags: Statistical Theory and Methods; Statistics and Computing/Statistics Programs; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences

Front Matter....Pages i-xxxi
Introduction and Motivation....Pages 1-11
Data and Statistics....Pages 13-27
Statistics Concepts....Pages 29-84
Graphs....Pages 85-121
Introductory Inference....Pages 123-165
One-Way Analysis of Variance....Pages 167-197
Multiple Comparisons....Pages 199-233
Linear Regression by Least Squares....Pages 235-262
Multiple Regression—More Than One Predictor....Pages 263-314
Multiple Regression—Dummy Variables, Contrasts, and Analysis of Covariance....Pages 315-344
Multiple Regression—Regression Diagnostics....Pages 345-375
Two-Way Analysis of Variance....Pages 377-426
Design of Experiments—Factorial Designs....Pages 427-478
Design of Experiments—Complex Designs....Pages 479-538
Bivariate Statistics—Discrete Data....Pages 539-576
Nonparametrics....Pages 577-592
Logistic Regression....Pages 593-629
Time Series Analysis....Pages 631-697
Back Matter....Pages 699-898