"""
Tools for calculating different types of statistics, such as effect size
estimates.
"""
import numpy as np
[docs]def cohens_d(g1_m, g1_sd, g1_n, g2_m, g2_sd, g2_n):
"""
Calculate Cohen's d for two independent samples.
This calculation involves taking the mean difference between groups, and
dividing it by the pooled standard deviation.
Parameters
----------
g1_m : float
Mean value for group 1.
g1_sd : float
Standard deviation for group 1.
g1_n : int
Sample size of group 1.
g2_m : float
Mean value for group 2.
g2_sd : float
Standard deviation for group 2.
g2_n : int
Sample size of group 2.
Returns
-------
d : float
Standardized effect size (Cohen's d) for the group difference.
"""
mean_diff = g2_m - g1_m
sd_num = ((g1_n - 1) * np.square(g1_sd)) + ((g2_n - 1) * np.square(g2_sd))
sd_denom = g1_n + g2_n - 2
sd_pooled = np.sqrt(sd_num / sd_denom)
return mean_diff / sd_pooled