Machine Learning Python
mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL. mlpy provides high-level functions and classes allowing, with few lines of code, the design of rich workflows for classification, regression, clustering and feature selection. mlpy is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License version 3. mlpy is available both for Python >=2.6 and Python 3.X.
An unlimited calculator for Chi Squared
This Chi Squared Calculator allows the user to enter any number of rows and columns, enter the observed frequencies used in the calculation, and the program will output the answer, as well as the degrees of freedom. This program runs on Python 3.2 ## BUT NO LONGER REQUIRES PYTHON to run! (Now in .exe form!) ## Sorry for the lack of floating point (Decimal) numbers support; attempting to input decimals will crash the program. Will fix soon! If you need any help, information, my email is: firstname.lastname@example.org
GUANO - Graphical User interface for performing ANalysis Of variance
Free and open source standalone program capable of conducting between, within, and mixed analyses of variance (ANOVA). Provides a simple graphical user interface for specifying analyses and interaction plots (analyses performed by http://code.google.com/p/pyvttbl/). Features: - Capable of high order factorial designs (> 2 factors) - Within and mixed analyses of variance provide corrections for violations of sphericity (Huynh-Feldt, Greenhouse-Geisser, Box) - A variety of data transformations can be applied (log10, reciprocal, arcsine, square-root, and Windsor) - Generalized eta-squared measures of effect size - Post-hoc power analysis (should match G*Power) - Outputs include tables of estimated marginal means - Up to 4-way interaction plots with errorbars (png, svg) - Confidence intervals account for within-subject variability (where applicable; Loftus and Masson, 1994) - Non-proprietary HTML output files - Non-proprietary codebase Gotchas: - Assumes balanced designs