Statistics::Distributions - Perl module for calculating critical values and upper probabilities of common statistical distributions

This Perl module calculates percentage points (5 significant digits) of the u (standard normal) distribution, the student's t distribution, the chi-square distribution and the F distribution. It can also calculate the upper probability (5 significant...

/Statistics-Distributions-1.02 - 01 Oct 2003 20:36:29 GMT

Statistics::Distributions::GTest - Perl implementation of the Log-Likelihood Ratio Test (G-test) of Independence.

The G-test of independence is an alternative to the chi-square test of independence for testing for independence in contingency tables. G-tests are coming into increasing use and as with the chi-square test for independence the G-test for independenc...

/Statistics-Distributions-GTest-0.1.5 - 02 Dec 2009 15:41:23 GMT

Statistics::Distributions::Ancova - Perl implementation of One-Way Analysis of Covariance for Independent Samples.

ANCOVA is a merger of ANOVA and regression for continuous variables. As with paired t-test and repeated-measures ANOVA this test removes the obscuring effects of pre-existing individual differences among subjects and thus may increase statistical pow...

/Statistics-Distributions-Ancova-0.32.2 - 01 Dec 2009 02:59:38 GMT

Statistics::Distributions::Bartlett - Bartlett's test for equal sample variances.

Bartlett test is used to test if k samples have equal variances. Such homogeneity is often assumed by other statistical tests and consequently the Bartlett test should be used to verify that assumption. See http://www.itl.nist.gov/div898/handbook/eda...

/Statistics-Distributions-Bartlett-0.0.2 - 27 Jan 2010 15:56:32 GMT

Math::SymbolicX::Statistics::Distributions - Statistical Distributions

This module offers easy access to formulas for a few often-used distributions. For that, it uses the Math::Symbolic module which gives the user an opportunity to manufacture distributions to his liking. The module can be used in two styles: It has a ...

/Math-SymbolicX-Statistics-Distributions-1.02 - 22 May 2006 11:29:36 GMT

Statistics::SDT - Signal detection theory (SDT) measures of sensitivity and bias in frequency data

This module implements algorithms for Signal Detection Theory (SDT) measures of sensitivity and response-bias, e.g., *d'*, *A'*, *c*, as based on frequency data. These are largely as defined in Stanislav & Todorov (1999; see REFERENCES), as well as o...

/Statistics-SDT-0.07 - 17 Mar 2018 02:49:50 GMT

Statistics::Gtest - calculate G-statistic for tabular data

"Statistics::Gtest" is a class that calculates the G-statistic for goodness of fit for frequency data. It can be used on simple frequency distributions (1-way tables) or for analyses of independence (2-way tables). Note that "Statistics::Gtest" will ...

/Statistics-Gtest-0.07 - 31 May 2008 14:01:31 GMT

Statistics::TTest - Perl module to perform T-test on 2 independent samples Statistics::TTest::Sufficient - Perl module to perfrom T-Test on 2 indepdent samples using sufficient statistics

Statistics::TTest This is the Statistical T-Test module to compare 2 independent samples. It takes 2 array of point measures, compute the confidence intervals using the PointEstimation module (which is also included in this package) and use the T-sta...

/Statistics-TTest-1.1.0 - 24 Jul 2003 05:33:16 GMT

Statistics::ANOVA - Parametric and nonparametric 1-way analyses of variance for means-comparison and clustering per differences/trends over independent or repeated measures of variables or levels

With that idea in mind, in order to actually perform an ANOVA, you really only need to define an analysis as based on (1) ordered or unordered predictors, (2) independent or repeated measurement of their effects on response variables (i.e., from diff...

/Statistics-ANOVA-0.14 - 17 Mar 2018 02:44:26 GMT

Statistics::Lmoments

This module is a thin wrapper around J. R. M. Hosking's FORTRAN library. For more information please see lmoments.ps in this distribution....

/Statistics-Lmoments-0.04 - 15 Sep 2015 15:16:23 GMT

Statistics::Normality - test whether an empirical distribution can be taken as being drawn from a normally-distributed population

Various situations call for testing whether an empirical sample can be presumed to have been drawn from a normally (Gaussian <http://en.wikipedia.org/wiki/Normal_distribution>) distributed population, especially because many downstream significance t...

/Statistics-Normality-0.01 - 20 Jan 2012 19:16:01 GMT

Statistics::ChisqIndep - The module to perform chi-square test of independence (a.k.a. contingency tables)

This is the module to perform the Pearson's Chi-squared test on contingency tables of 2 dimensions. The users input the observed values in the table form and the module will compute the expected values for each cell based on the independence hypothes...

/Statistics-ChisqIndep-0.1 - 24 Aug 2005 20:43:38 GMT

Statistics::MaxEntropy - Perl5 module for Maximum Entropy Modeling and Feature Induction

This module is an implementation of the Generalised and Improved Iterative Scaling (GIS, IIS) algorithms and the Feature Induction (FI) algorithm as defined in (Darroch and Ratcliff 1972) and (Della Pietra et al. 1997). The purpose of the scaling alg...

/Statistics-MaxEntropy-1.0 - 26 Jul 2015 20:01:13 GMT

Sys::Statistics::Linux - Front-end module to collect system statistics

Sys::Statistics::Linux is a front-end module and gather different linux system information like processor workload, memory usage, network and disk statistics and a lot more. Refer the documentation of the distribution modules to get more information ...

/Sys-Statistics-Linux-0.66 - 09 Mar 2012 03:11:37 GMT

Statistics::Descriptive - Module of basic descriptive statistical functions.

This module provides basic functions used in descriptive statistics. It has an object oriented design and supports two different types of data storage and calculation objects: sparse and full. With the sparse method, none of the data is stored and on...

/Statistics-Descriptive-3.0702 - 25 Oct 2018 18:12:21 GMT

Bundle::Math::Statistics - Bundle of modules related to statistics

This is a bundle of modules related to statistics. Please have a look at Bundle::Math. If you would like to see a specific module included in a future version of this bundle, please send me an email or use rt.cpan.org....

/Bundle-Math-Statistics-1.01 - 10 Jul 2004 06:58:21 GMT

Statistics::MVA::Bartlett - Multivariate Test of Equality of Population Covariance Matrices.

Bartlett's test is used to test if k samples have equal variances. This multivariate form tests for homogeneity of the variance-covariance matrices across samples. Some statistical tests assume such homogeneity across groups or samples. This test all...

/Statistics-MVA-Bartlett-0.0.4 - 26 Jan 2010 18:51:22 GMT

Statistics::DependantTTest - Perl module to perform Student's dependant or paired T-test on 2 paired samples.

This is the statistical T-Test module to compare 2 paired data sets. It takes 2 arrays of values and will return the t value and degrees of freedom in order to test the null hypothesis. The t values and degrees of freedom may be correlated to a p val...

/Statistics-DependantTTest-0.03 - 21 May 2003 09:53:37 GMT

Statistics::FactorAnalysis - A Perl implementation of Factor Analysis using the Principal Component Method.

Factor analysis is a statistical method by which the variability of a large set of observed variables is described in terms of a smaller set of unobserved variables termed factors. Factor analysis uses the premise that data observed from such a large...

/Statistics-FactorAnalysis-0.0-2 - 18 Dec 2009 00:38:34 GMT

Statistics::PointEstimation - Perl module for computing confidence intervals in parameter estimation with Student's T distribution Statistics::PointEstimation::Sufficient - Perl module for computing the confidence intervals using sufficient statistics

Statistics::PointEstimation This module is a subclass of Statistics::Descriptive::Full. It uses T-distribution for point estimation assuming the data is normally distributed or the sample size is sufficiently large. It overrides the add_data() method...

/Statistics-TTest-1.1.0 - 24 Jul 2003 05:33:16 GMT

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