|For general academic resources which may
contain Statistics related materials as well as from other
Alternative Methods for Collecting Evaluation
This material is based upon work supported by the
Cooperative State Research, Education, Extension Service, U.S.
Department of Agriculture, and the Cooperative Extension
Service, University of Arizona.
The American Religion Data Archive
is a project funded by the
Lilly Endowment, Inc. and acts to preserve quantitative data on
American religion, to improve access to this data, to increase
the use of the data, and to allow comparisons across data files.
The ARDA collection includes data on churches and church
membership, religious professionals, and religious groups
(individuals, congregations and denominations).
The Electronic Journal of Probability
The Electronic Journal of Probability publishes full-size
research articles in probability theory. The
Electronic Communications in Probability (ECP), a sister
journal of EJP, publishes short notes, survey articles, and
research announcements in probability theory. The Electronic
Journal of Probability is affiliated with the Institute of
Glossary of Social Science Computer and
Social Science Data Terms
glossary includes terms which you may find useful in
managing data collections and providing basic data services. It
does not attempt to cover all social science research terms or
all computer terms. From UCSD.
Guide to Questionnaires and Surveys
web site, you will find information related to the creation
of surveys and questionnaires. The information is classified
into 5 topics. Each topic presents a choice of articles. Each
one is about a problem that can be experienced by someone
engaged in a procedure of data collection with a survey. Note:
beware of pop-ups. This is a Tripod site.
David Lane, The author of this Online
text and resource guide is an Associate Professor of
Psychology, Statistics, and Management at Rice University
Mixed Method Evaluations
Mixed Method Evaluations was initiated because of the
recognition that by focusing primarily on quantitative
techniques, evaluators may miss important parts of a story.
Experienced evaluators have found that most often the best
results are achieved through the use of mixed method
evaluations, which combine quantitative and qualitative
techniques. From the NSF.
Pitfalls of Data Analysis
Pitfalls of Data Analysis discusses things that people often
overlook in their data analysis, and ways people sometimes "bend
the rules" of statistics to support their viewpoint. It also
discusses ways you can make sure your own statistics are clear
and accurate. Includes examples from medicine, education, and
industry. By Clay Helberg, M.S. Research Design and Statistics
Unit University of Wisconsin Schools of Nursing and Medicine
Selecting Statistics is an online program that guides
researchers to the proper statistical technique by answering
questions about their data. A simple and elegant tool based on A
Guide for Selecting Statistical Techniques for Analyzing Social
Science Data, 2nd Ed. Survey Research Center, Institute for
Social Research, The University of Michigan.
Statistical Good Practice Guidelines
Statistical Good Practice Guidelines is a series of guides
on good statistical practice, intended primarily to give help to
research and support staff in development projects. The guides
are available to view online or to download for printing and
reading offline. From the University of Reading.
Statistical Resources on the Web
Statistical Resources on the Web from the University of
Michigan is a one stop data clearing house offering updated
links to a large variety of data sources.
Statistics Glossary either alphabetically or by area.
The web pages listed
here comprise a powerful, conveniently-accessible,
multi-platform statistical software package. There are also
links to online statistics books, tutorials, downloadable
software, and related resources. All of these resources are
Virtual Data Center
Center is an operational, open-source,
digital library to enable the sharing of quantitative research
data, and the development of distributed virtual collections of
data and documentation. A joint project of the
Harvard-MIT Data Center and the Harvard University