gbtest - Online in the Cloud

PROGRAM:

NAME

gbtest - Compute statistical tests on data

SYNOPSIS

gbtest [options] <tests list>

DESCRIPTION

Compute statistical tests on data. Each test is specified by a unique name and optional
parameters follows, separated by commas. Depending on the test, one, two or three columns
of data are expected. '1 sample' tests expect a single columns. Test on 'pairs' expect two
columns of equal length. Test on '2 samples' expect two columns of data, possibly of
different length. Test on 2+ and 3+ samples expect a varying number of columns. If more
columns are provided, the test is repeated for any column in the case of 1 sample test,
and any couple of columns in the case of 2 sample tests. In the last case, the output is
expressed in matrix format, with estimated statistics on the lower triangle and p-scores
(if requested) on the upper. The removal of 'nan' entries is automatic, and is performed
consistently with the nature of the test.

Tests typically assume 1, 2 or 3+ samples. Available tests are:

D+,D-,D,V 1 samp
Kolmogorov-Smirnov tests on cumulated data

W2,A2,U2
1 samp Cramer-von Mises tests on cumulated data

CHI2-1 1 samp Chi-Sqrd, 1 samp. 2nd column: th. prob.

WILCO 1 samp Wilcoxon (mode=0)

TS 1 samp Student's T (mean=0)

TR-TP 1 samp Test of randomness: turning points

TR-DS 1 samp Test of randomness: difference sign

TR-RT 1 samp Test of randomness: rank test

R pairs Pearson's correlation coefficient

RHO pairs Spearman's Rho rank correlation

TAU pairs Kendall's Tau correlation

CHI2-2 pairs Chi-Sqrd, 2 samples

KS 2 samp Kolmogorov-Smirnov test

T 2 samp Student's T with same variances

TH 2 samp Student's T with different variances

F 2 samp F-Test for different variances

WMW 2 samp Wilcoxon-Mann-Whitney U

FP 2 samp Fligner-Policello standardized U^

LEV-MEAN
2+ samp Levene equality of variances using means

LEV-MED
2+ samp Levene equality of variances using medians

KW 3+ samp Kruscal-Wallis test on 3+ samples

CHI2-N 3+ samp Multi-columns contingency table analysis

OPTIONS

-p compute associated significance

-s input data are already sorted

-F specify the input fields separators [" \t"]

-v verbosity: 0 just results, 1 headings, 2+ description [0]

-h this help

EXAMPLES

gbtest FP < file
compute the Fligner-Policello test on the columns of 'file', considering all
possible pairings.

gbtest KW -p < file
compute the Kruscal-Wallis test and its p-score on the first three columns of data
in 'file'

Use gbtest online using onworks.net services