P-value generator

import numpy as np
from scipy.stats import ttest_ind

# simulated experiments
# two conditions, 50 observations per condition
# standardized effect size randomly chosen between 0 and .5
for i in np.arange(0,10):
    sample_size = 50
    effect_size = np.random.uniform(0,.5,1)
    group_1 = np.random.normal(loc=0.0, scale=1.0, size=sample_size)
    group_2 = np.random.normal(loc=effect_size, scale=1.0, size=sample_size)
    t, p = ttest_ind(group_1, group_2, equal_var=False)
    if p < .05:
        print("p = %g" % (round(p,3)) + '. Statistically significant! #pvalues #nhst #statistics')
    else:
        print("p = %g" % (round(p,3)) + '. Not statistically significant! #pvalues #nhst #statistics')