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Statistical Computing Environments for Social Research
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Statistical Computing Environments for Social Research

Edited by:


October 1996 | 256 pages | SAGE Publications, Inc
The nature of statistics has changed from classical notions of hypothesis testing, towards graphical and exploratory data analysis which exploits the flexibility of interactive computing and graphical displays. This book describes seven statistical computing environments - APL2STAT, GAUSS, Lisp-Stat, Mathematica, S, SAS/IML, and Stata - which can be used effectively in graphical and exploratory modeling.

These statistical computing environments, in contrast to standard statistical packages, provide programming tools for building other statistical applications. Programmability, flexible data structures, and - in the case of some of the computing environments - graphical interfaces and object-oriented programming, permit researchers to take advantage of emerging statistical methodologies.

Three additional chapters, describing the Axis, R-code and ViSta statistical packages, demonstrate how researchers have extended one of the computing environments - Lisp-Stat - to produce significant statistical applications employing graphical interfaces to statistical software.

Robert Stine and John Fox
Editors' Introduction
 
PART ONE: COMPUTING ENVIRONMENTS
John Fox and Michael Friendly
Data Analysis Using APL2 and APL2STAT
J Scott Long and Brian Noss
Data Analysis Using GAUSS and Markov
Luke Tierney
Data Analysis Using Lisp-Stat
Robert Stine
Data Analysis Using Mathematica
Charles Hallahan
Data Analysis Using SAS
Lawrence C Hamilton and Joseph M Hilbe
Data Analysis Using Stata
Daniel A Schulman, Alec D Campbell, and Eric C Kostello
Data Analysis Using S-Plus
 
PART TWO: EXTENDING LISP-STAT
Robert Stine
AXIS
An Extensible Graphical User Interface for Statistics

 
Sanford Weisberg
The R-Code
A Graphical Paradigm for Regression Analysis

 
Forrest W Young and Carla M Bann
ViSta
A Visual Statistics System

 

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