Package provides the implementation of various statistics distribution such as normal distribution, fisher, student-t, and so on
-
Normal Distribution
- cumulativeProbability(Z)
- invCumulativeProbability(p)
-
Student's T Distribution
- cumulativeProbability(t_df)
- invCumulativeProbability(p)
-
Fisher–Snedecor Distribution
- cumulativeProbabiliyt(F)
-
Chi-Square Distribution
- cumulativeProbabiliy(ChiSquare)
Run the following npm command to install
npm install js-stats
Sample code is available at playground
jsstats = require('js-stats');
//====================NORMAL DISTRIBUTION====================//
var mu = 0.0; // mean
var sd = 1.0; // standard deviation
var normal_distribution = new jsstats.NormalDistribution(mu, sd);
var X = 10.0; // point estimate value
var p = normal_distribution.cumulativeProbability(X); // cumulative probability
var p = 0.7; // cumulative probability
var X = normal_distribution.invCumulativeProbability(p); // point estimate value
//====================T DISTRIBUTION====================//
var df = 10; // degrees of freedom for t-distribution
var t_distribution = new jsstats.TDistribution(df);
var t_df = 10.0; // point estimate or test statistic
var p = t_distribution.cumulativeProbability(t_df); // cumulative probability
var p = 0.7;
var t_df = t_distribution.invCumulativeProbability(p); // point estimate or test statistic
//====================F DISTRIBUTION====================//
var df1 = 10; // degrees of freedom for f-distribution
var df2 = 20; // degrees of freedom for f-distribution
var f_distribution = new jsstats.FDistribution(df1, df2);
var F = 10.0; // point estimate or test statistic
var p = f_distribution.cumulativeProbability(F); // cumulative probability
//====================Chi Square DISTRIBUTION====================//
var df = 10; // degrees of freedom for cs-distribution
var cs_distribution = new jsstats.ChiSquareDistribution(df);
var X = 10.0; // point estimate or test statistic
var p = cs_distribution.cumulativeProbability(X); // cumulative probability