On-line resources in statistics
public-domain statistical software:
Comprehensive archive of public domain statistical software,
datasets and news maintained by the Department of Statistics at
Carnegie Mellon University.
Guide to Available Mathematical
Access to dozens of packages in NETLIB & elsewhere organized
through a problem decision tree. From the National Institute of
Standards and Technology.
Large collection of commercial and public software used in
econometrics including regression, time series analysis, Bayesian
analyses, linear modeling, limited-dependent variables (i.e. censoring
& truncation), optimization, and links to other metasites. From the
Econometrics Journal online.
Advanced Visual Systems (AVS)
International AVS Centre clearinghouse for visualization
software, with over 900 public domain modules.
commercial statistical software:
Lists of commercial statistical packages, from the
University of Koln.
Science Plus Group
European commercial distributor of several hundred packages
analysis in the social and behavioral sciences. Includes structural
regression modeling, multivariate analysis, survival analysis,
bootstrap and jackknife analysis, general statistics, data mining, GIS,
classification, and more.
to statistical software
Links to SAS, Matlab, Minitab, BMDP, SPSS, S-Plus,
and others from the Departments of Statistics at George Mason
Metasites to Web resources on
statistics (societies, journals, departments, on-line courses
and textbooks, commercial and public domain software, etc.):
and Statistical Graphics Resources
Award-winning annotated, topic-based collection of available
resources for statistics, statistical graphics, and computation related
to research, data analysis and teaching with ~600 links. From the
Statistical Consulting Service of York University.
A large list of (some fully on-line) texts, courses, tutorials,
glossaries, Java demonstrations, graphics, datasets, etc. by Juha
Puranen of University of Helsinki.
Comprehensive collection of links to statistical resources on
Internet including software
libraries, journals, departments and organizations, SAS/S+ software,
forecasting and neural network information, and more. From
Charlie Hallahan of the US Dept. of Agriculture.
Virtual Library: Statistics
Data sources, job announcements, organizations &
archives, software vendors, journals,email lists & news groups.
From the Department of Statistics at University of Florida.
on the Web
Dr. Arsham's online statistics course.
Lists of statistical societies, departments, agencies, jobs,
journals and software. From the Centre for Statistics of University of
statistical meetings and workshops:
from the American Statistical Association
from the international Institute of Mathematical Statistics
calendar from the Society for Industrial and Applied Mathematics
CSDA SSN from the
Statistical Software Newsletter of the Computational Statistics &
Data Analysis division of the International Statistics Institute
for the fields of statistical
pattern recognition, classification, neural networks, machine vision
and learning, data mining, image processing, mathematical morphology:
Discovery and data mining (Katholieke)
Recognition Files (Delft)
(DataMine.com TWiki site)
Processing Library (Intel)
vision software (Carnegie-Mellon)
Society of North America
for Bayesian statistical methods:
inference for the physical sciences (BIPS)
Annotated metasite with informative background on Bayesian
statistics and its applications in astronomy & physics.
Provides links to texts, tutorials, articles, software, and on-line
resources. By Thomas Loredo, Cornell University.
Comprehensive on-line text emphasizing multivariate analysis
advanced topics such as data mining, machine learning, regression
splines, neural networks, survival analysis, time series
analysis. From StatSoft.
Introductory on-line textbook by David Lane of Rice University.
Well-organized elementary text designed for engineers with
software package. From the National Institute for Standards and
Data Analysis Briefbook
A condensed handbook, or extended glossary, of several dozen
statistics and related fields for physicists. An award-winning
resource by R. Bock and W. Krisher at CERN.
& statistical data analysis
Notes from an four-week postgraduate crash course for particle
physicists by Glen Cowan (Univ. of London). Topics include probability
theory and functions, Monte Carlo methods, frequentist statistical
tests and parameter estimation, maximum likelihood and least squares
estimators, confidence intervals and limits, and unfolding instrumental
response functions. Codes are in C++.
On-line textbook covering basic statistics, multivariate
analysis, clustering and classification, data ining, experimental
design, linear regression and nonlinear estimation, nonparametrics,
quality control, survival analysis, time series and more. From