As some of you might know, I've been writing code for statistics in Python for some time. I also have a repository on Github which is the basis of a book I've been writing for several years.

There's a lot there including modules for unit testing. If you want to join in, feel free to fork or email changes in to me if you prefer.

https://github.com/salmoni/CompStatsPython

And for the eagle-eyed amongst you, there's some basic stats stuff in Prolog too! See stats.pl here

List of descriptives:

And others such as

There's a lot there including modules for unit testing. If you want to join in, feel free to fork or email changes in to me if you prefer.

https://github.com/salmoni/CompStatsPython

And for the eagle-eyed amongst you, there's some basic stats stuff in Prolog too! See stats.pl here

List of descriptives:

- VSort - sort a vector
- MSort - sort a numpy.matrix
- CalculateRanks - for calculating the ranks of a numpy.matrix
- GetSSCP_M - calculates the sum of squares and cross-products numpy.matrix
- GetVarsCovars_M - calculates the variances and covariances numpy.matrix
- GetVariances - calculates the variances of a numpy.matrix of variables
- GetStdDevs - calculates the standard deviations of a numpy.matrix of variables
- GetCorrelationMatrix - calculates the correlation numpy.matrix
- Count - returns the number of non-missing data
- sum - returns the sum of non-missing data
- minimum - returns the minimum of non-missing data
- maximum - returns the maximum of non-missing data
- Range - maximum minus the minimum
- proportions -
- relfreqmode -
- cumsum -
- cumproduct -
- cumpercent -
- frequencies -
- trimmeddata -
- trimmedmean -
- bitrimmedmean -
- mean -
- median -
- mode -
- moment -
- TukeyQuartiles - returns Tukey's hinges
- MooreQuartiles - returns Moore & McCabe's hinges
- SPQuantile - quantile used by S-Plus
- TradQuantile - quantile used by SPSS
- MidstepQuantile - mid-step qua
- Q1 - Q1 quantile from Hyndnumpy.man & Fan
- Q2 - Q2 quantile from Hyndnumpy.man & Fan
- Q3 - Q3 quantile from Hyndnumpy.man & Fan
- Q4 - Q4 quantile from Hyndnumpy.man & Fan
- Q5 - Q5 quantile from Hyndnumpy.man & Fan
- Q6 - Q6 quantile from Hyndnumpy.man & Fan
- Q7 - Q7 quantile from Hyndnumpy.man & Fan
- Q8 - Q8 quantile from Hyndnumpy.man & Fan
- Q9 - Q9 quantile from Hyndnumpy.man & Fan
- InterquartileRange -
- SS - sum of squares
- SSDevs - sum of squared deviations from the mean
- SampVar - sample variance
- PopVar - population variance
- SampStdDev - sample standard deviation
- PopStdDev - population standard deviation
- StdErr - standard error
- CoeffVar - coefficient of variation
- ConfidenceIntervals - returns the confidence intervals
- numpy.maD - Median absolute deviation
- GeometricMean - the geometric mean
- HarmonicMean - the harmonic mean
- MSSD - mean square of successive differences
- Skewness - returns the skewness
- Kurtosis - returns the kurtosis
- StandardScore - transforms a vector into a standard (ie, z-) score
- EffectSizeControl - returns an effect size if a control condition is present
- EffectSize - returns an effect size if no control is present
- FiveNumber - Tukey's five number sumnumpy.mary (minimum, lower quartile, median, upper quartile, maximum)
- OutliersSQR - returns two arrays, one of outliers defined by 1.5 * IQR, and the other without these outliers

And others such as

- Cronbach's Alpha
- Kruskal-Wallis
- Multiple regression
- Mann-Whitney U
- Wilcoxon
- ANOVA

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