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A short version of this article first appeared in the International Statistical Association newsletter, Vol 26, Number 1 (76), 2002, and is at http://isi.cbs.nl/NLet/NLet021-04.htm and http://isi.cbs.nl/FreeTools.htm
There is a great deal of research methods information available for
free on the WEB. Information includes data or data sets, and also
general statistical textbooks, email lists, software, and many sites
about
special topics, such as epidemiology, forecasting, data presentation,
data
editing, multiple imputation, and propensity score analysis. This
article is a brief review of some useful sites covering these topics.
There are several sites that are general links. One of these is the Intute statistics page, http://www.intute.ac.uk/socialsciences/statistics/ which also has sub-pages on demography, international, local, national, official and regional statistics, and statistical theory. The Intute site has a variety categories, such as data, educational material, government sites, mailing lists and societies. One other general site is Betty Jung's statsites http://www.bettycjung.net/Statsites.htm .
The best place to start for learning about statistics is HyperStatistics
Online, at http://davidmlane.com/hyperstat/index.html.
This is the best place it is a a nice statistics book, and it is a
comprehensive
list of other on line statistics books. Most of these are basic
to
intermediate. One book, the Statsoft text,
http://www.statsoft.com/textbook/stathome.html
has fairly advanced topics. Another, Statistics at square
one http://www.bmj.com/statsbk/
is a fairly introductory book.
Since statistics is difficult to learn and it is not always clear to the general public how statistics may be useful, there are several projects aimed at educating the public. One is the International Statistical Literacy Project http://www.stat.auckland.ac.nz/~iase/islp/ The mission of this project "is to support, create and participate in statistical literacy activities and promotion around the world." Also, the International Statistical Institute http://isi.cbs.nl/ is preparing "Statistics in public life", which looks to be interesting. The American Statistical Association http://www.amstat.org/. also links to a variety of resources about teaching, at all grade levels.
There is also tons of free software on the net. The best place
to find free statistical software is the Free Statistical Software
site at http://statpages.org/javasta2.html.
This site lists general purpose software, as well as software devoted
to
specific purposes, such as curve fitting, epidemiology, surveys, and
programming.
There are also brief descriptions of each package. We also list
software packages on our page http://gsociology.icaap.org/methods/soft.html
along with a list of other sites that list free statistical
packages. One great site
about learning how to use statistical software is the Statistical
Computing
site, at http://www.ats.ucla.edu/stat/default.htm.
They have a large number of links, how to's and other material, mostly
for commercial packages. One review of free statistical software
is here http://en.citizendium.org/wiki/Free_statistical_software
which briefly describes the history, quality, functions and
limits of a number of free packages.
There are a number of email lists. Allstat, at https://www.jiscmail.ac.uk/cgi-bin/webadmin?A0=allstat is a general list, although a great deal of the postings appear to be postings about jobs or training courses. Another list stat-l, at http://lists.mcgill.ca/archives/stat-l.html focuses more on statistical questions. Another useful list, not on Allstat, is Epidemio, at http://www.listes.umontreal.ca/wws/info/epidemio-l This list is about epidemiology.
There are a number of comprehensive places to look for data.
One is Statistical
Resources on the Web
http://www.lib.umich.edu/govdocs/stats.html.
This is a comprehensive guide to data on many topics, including health,
demographics, labor, economics, environment, and much more. Another
starting
point for social, political and economic data is the Global Social
Change Research Project http://gsociology.icaap.org/,
which has both links to a very large number of other data link sites,
and a page of data sets compiled or created from other data sets. Many
of the data sets listed on this project site are public domain. This UN
site http://data.un.org/
has data on nearly every topic, from the UN and it's various
associates. This UN site http://unstats.un.org/unsd/methods/inter-natlinks/sd_natstat.asp
and this BLS
site http://www.bls.gov/bls/other.htm
link to national statistical centers of most countries of the world.
Not all data sets are free to use. Some will charge
for use, and you generally have to check each one.
There are resources about dozens of specific topics on the web. Some of these topics include epidemiology, graphical analysis and presentation, missing data, forecasting, gathering data and meta-analysis.
Epidemiology: The two best places to start for epidemiology
are EpiMonitor, http://www.epimonitor.net/index.htm,
which has a very comprehensive list of links and the WWW Virtual
Library: Epidemiology http://www.epibiostat.ucsf.edu/epidem/epidem.html
another gateway. Another very good
place
to start is epidemiolog, at http://www.epidemiolog.net/.
This site also has a fairly comprehensive listing of epidemiology
sites,
as well as an on-line textbook. First time visitors should start
at http://www.epidemiolog.net/evolving/
. Another free on-line textbook is Epidemiology
for the Uninitiated, at http://www.bmj.com/epidem/epid.html.
A very good place to find world
epidemiological data, reports, issues and information is from
WHO http://www.who.int/topics/epidemiology/en/
which includes for example the 10 leading causes of death, and
the Weekly Epidemiological Record.
There are also three interesting sites for learning
epidemiology. One is the Epidemiology Supercourse,
http://www.pitt.edu/~super1/,
which is a set of on line lectures on various epidemiology
courses.
These lectures can be downloaded and used, whole or in part, in your
own
lectures. The North Carolina Center for Public Health
Preparedness
Training Website http://nccphp.sph.unc.edu/training/
has free on line training for biostatistics, epidemiology, other
topics.
You can get certificates for each class you complete. Each class is 1/2
to 1 hour.
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Graphics: After analyzing data, it is very helpful to know how to best present the results. Very good sites are: Informative Presentation of Tables, Graphs and Statistics, at http://www.rdg.ac.uk/ssc/publications/guides/toptgs.html ,Washington Statistical Society Methodology Seminars, Data Presentation: A Guide To Good Graphics http://www.scs.gmu.edu/~wss/methods/zawitzg.html and Presenting Data http://lilt.ilstu.edu/gmklass/pos138/datadisplay/ . Also BTS’s Guide to Good Statistical Practice has a useful section on presenting results, at http://www.bts.gov/publications/guide_to_good_statistical_practice_in_the_transportation_field/index.html . For some interesting good and bad examples, see the Gallery of Data Visualization, at http://www.math.yorku.ca/SCS/Gallery/
Missing Data: Two sites that are overviews of missing data page are the University of Texas Statistical Services FAQ page, #25, at http://www.utexas.edu/its-archive/rc/answers/general/gen25.html and Cornell's Office of Statistical Computing FAQ page, http://www.osc.cornell.edu/news/archive.php specifically FAQ #46 and #47. One way to deal with missing data is multiple imputation, described at the Multiple Imputation FAQ page, at http://www.stat.psu.edu/~jls/mifaq.html. Multiple imputation fills in missing data by using other variables to predict the missing values. This method is also described at Joseph Schafer’s site, in a 1999 article "Multiple imputation: a primer". at http://www.stat.psu.edu/~jls/index.html. One software program for estimating missing data is AMELIA, at http://gking.harvard.edu/stats.shtml
Forecasting: Two faculty members have lectures about
forecasting
on the web. These are Bob Nau's class notes on forecasting
at http://www.duke.edu/~rnau/411out00.html,
and
Hossein Arsham's Time Series Analysis and Forecasting Techniques,
at http://home.ubalt.edu/ntsbarsh/Business-stat/stat-data/Forecast.htm
Also, another forecasting site is the Federal Forecasters Consortium,
at http://www1.va.gov/vhareorg/ffc.htm
Conference proceedings can be downloaded from this site.
Methods of gathering data: There are a number of sites on gathering data. Two places to start are Resources for Methods in Evaluation and Social Research, at http://gsociology.icaap.org/methods/ and The World Wide Evaluation Information Gateway http://www.policy-evaluation.org/ These site are link to other sites about methods, quantitative and qualitative. Some sites are about specific tools in data gathering. The Statnotes site has a section on survey methods, at http://faculty.chass.ncsu.edu/garson/PA765/survey.htm Tom O'Connor's lecture notes, at http://www.apsu.edu/oconnort/3760/3760lects.htm covers various issues such as measurement, validity and reliability, and scales in indexes.
Meta-analysis: There are several introductions to
meta-analysis.
One is a BMJ site, Meta-Analysis, Education and debate http://www.bmj.com/collections/ma.htm
a collection of chapters describing methods and issues. One link
is
to an on line book Meta - Analysis: Methods of Accumulating Results
Across Research Domains, by Larry C. Lyons, at http://www.lyonsmorris.com/MetaA/index.htm
(this link sometimes doesn't work).
One of the Epi
Supercourses
is about meta-analysis, How to conduct a Meta-Analysis http://www.pitt.edu/~super1/lecture/lec1171/index.htm
Another site is The Meta Analysis of Research
Studies http://echo.edres.org:8080/meta/
which is an overview and links
to documents and resources.
Public education about statistics. Three papers about
how
to read papers are: How to read a paper: Statistics for the
non-statistician.
I: Different types of data need different statistical tests.
Trisha Greenhalgh, BMJ 1997;315:364-366 (9 August) http://www.bmj.com/cgi/content/full/315/7104/364How
to read a paper: Statistics for the non-statistician. II:
"Significant"
relations and their pitfalls. By Trisha Greenhalgh,
BMJ
1997;315:422-425 (16 August) http://www.bmj.com/cgi/content/full/315/7105/422
and How to read a paper: Papers that go
beyond numbers http://www.bmj.com/cgi/content/full/315/7110/740
Article by Trisha Greenhalgh Rod Taylor, in BMJ 1997;315:740-743 (20
September).
Also,
the American Statistical Association has an on line journal, the
Journal
of Statistical Education, at http://www.amstat.org/publications/jse/
which has free articles about teaching statistics. This
organization Consortium for the Advancement of Undergraduate
Statistics Education at http://www.causeweb.org/
also
has a great many links to texts, notes, journals, data sets, etc, in
particular in the resources section.
Other topics include a paper by Rubin explaining propensity
score
analysis, at http://www.symposion.com/nrccs/rubin.htm.
Propensity score analysis is a method of dealing with self selection
bias.
Also, the Federal Committee on Statistical Methodology, at http://www.fcsm.gov/reports/
, has some interesting papers, especially RL2. Record Linkage
Techniques
- 1997: Proceedings of an International Workshop and Exposition.
(This is RL2, not RL1.) Another interesting special topic
sit
is the Centre for Multilevel Modelling at http://www.cmm.bristol.ac.uk/
One site about data mining is kdnuggets at http://www.kdnuggets.com/
(a newsletter and general links to links site).
I don't necessarily endorse any of the sites listed here, and do not
assume responsibility for content of the web sites listed in this
article.
This article is solely presented for educational purposes.
last updated 6/21/09
last verified 6/21/09
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