Statistical Computing Environments for Social Research
β Scribed by Robert A. Stine (editor), John Fox (editor)
- Publisher
- SAGE Publications, Inc
- Year
- 1996
- Tongue
- English
- Leaves
- 260
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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 res
π SIMILAR VOLUMES
Wiley, 2013. β 560 p. β ISBN 978-1-118-23415-0<div class="bb-sep"></div>A core statistics text that emphasizes logical inquiry, not math.<div class="bb-sep"></div>Basic Statistics for Social Research teaches core general statistical concepts and methods that all social science majors must master to
STATISTICS: A TOOL FOR SOCIAL RESEARCH, Eighth Edition, is a comprehensive, reader-friendly text that uses real-world examples, engaging exercises, and special features in every chapter to help even the most math-averse students succeed in a required statistics course. At the same time, this versati
Statistics: A Tool for Social Research, Third Canadian Edition, helps to construct and develop the skills necessary for social science majors to become statistically literateβcomputational competence, appreciation of statistics, and the ability to read professional social science literatureβfrom a u
STATISTICS: A TOOL FOR SOCIAL RESEARCH, Ninth Edition, is a comprehensive, reader-friendly text that uses real-world examples, engaging exercises, and special features in every chapter to help even the most math-averse students succeed in a required statistics course. At the same time, this versatil