Python

cohensd_2ind

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Calculate cohen’s d for 2 independent samples. See Using_cohens_d.ipynb for a notebook of given examples.

Syntax

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import cohens_d as cD

d = cD.cohensd_2ind(inarg1, inarg2)

Description

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A

d = cD.cohensd_2ind(group1, group2) returns cohen’s d for 2 independent samples. example

Examples

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Example 1

Generate some random data and find cohen’s d.

import numpy as np 

group1 = np.random.normal(0, 1, (100,))
group2 = np.random.normal(1, 1, (150,))
cD.cohensd_2ind(group1, group2)

d = 1.035420225827119

Input Arguments

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group1

Data vector for group 1.

Vector of data to calculate cohen’s d for 2 independent samples.

Data Types: (numeric, vector)

group2

Data vector for group 2.

Vector of data to calculate cohen’s d for 2 independent samples.

Data Types: (numeric, vector)

Output

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d

Effect size.

Cohen’s d effect size for 2 independent samples.

Data Types: (scalar, float, numeric)

More About

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Lecture

I refrained from outputting size of effect (e.g., ‘small’, ‘medium’, ‘large’) because these are arbitrary and should be thought of as such.

Tips

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Issues and Discussion

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Issues and Discussion.

If you don’t know how to use github (or don’t want to), just send me an email.