OStats is a simple tool for data visualisation and statistical analysis, particularly aimed at helping students learn statistics.
OStats is a simple tool for data visualisation and statistical analysis, particularly aimed at helping students learn statistics.
DataFerrett is a unique data analysis and extraction tool -- with recoding capabilities -- to customize federal, state, and local data to suit your requirements. Using DataFerrett, you can develop an unlimited array of customized spreadsheets that are as versatile and complex as your usage demands. The DataFerrett helps you locate and retrieve the data you need across the Internet to your desktop or system, regardless of where the data resides. You can then develop and customize tables. Selecting your results in your table you can create a chart or graph for a visual presentation into an html page. Save your data in the databasket and save your table for continued reuse. The DataFerrett is a Beta testing version that will incorporate the latest bug fixes, enhancements, and new functionality that will be rolled into the DataFerrett after testing has been completed.
The BUGS (Bayesian inference Using Gibbs Sampling) project is concerned with flexible software for the Bayesian analysis of complex statistical models using Markov chain Monte Carlo (MCMC) methods. This site is primarily concerned with the stand-alone WinBUGS 1.4.1 package, which has a graphical user interface and on-line monitoring and convergence diagnostics. This program can be downloaded for free from the site.
This general, introductory tutorial on mathematical modeling (in pdf format) is intended to provide an introduction to the correct analysis of data. It addresses, in an elementary way, those ideas that are important to the effort of distinguishing information from error. This distinction constitutes the central theme of the material described herein. Both deterministic modeling (univariate regression) as well as the (stochastic) modeling of random variables are considered, with emphasis on the latter. No attempt is made to cover every topic of relevance. Instead, attention is focussed on elucidating and illustrating core concepts as they apply to empirical data.