`dataFrame.columns.stat — cohensD()`

Description

The cohensD() method of the stat object computes Cohen's d effect size for two selected columns.

Signature

dataFrame.columns(...columnNames).stat.cohensD({ comparison: 'independent', estimator: 'sample' })

Scope: columns
Family: stat
Returns: number

Arguments

...columnNames ( string[] ): The name of the columns from which to compute Cohen's d effect size
options (object): Cohen's d computation options.

Options

comparison (string)

The comparison method used to compute Cohen's d.

independent (default)
paired

estimator (string)

The variance estimator used in the calculation.

population
sample (default)

Returns

effectSize (object): The computed Cohen's d effect size.

Notes

The method requires exactly two selected columns.
The independent comparison computes Cohen's d using the difference between the means of two independent samples.
The paired comparison computes Cohen's d using the paired differences between observations.
Positive values indicate that the first selected column has a larger mean than the second selected column.
Negative values indicate that the second selected column has a larger mean than the first selected column.
Common interpretation guidelines for the absolute value of Cohen's d are:

< 0.2 : negligible
0.2 – 0.5 : small
0.5 – 0.8 : medium
≥ 0.8 : large

Example

// calculate the Cohen's d effect size between 2 columns of the dataFrame
var effectSize = dataFrame.columns('groupA', 'groupB').stat.cohensD();

// log the effect size
notebook.log(effectSize);