Shortcuts for some common statistical functions
Here are some useful functions when performing statistical analysis: Confidence Interval from scipy import stats from numpy import mean, var from math import sqrt sample = [1, 2, 3, 4, 5] #95% confidence interval R = stats.t.interval(0.95, len(sample)-1, loc=mean(sample), scale=sqrt(var(sample)/len(sample))) >>> R (1.2440219338298311, 4.7559780661701687) SciPy documentation Correlation Coefficient from numpy import corrcoef x = [1, 2, 3, 4, 100] y = [6, 7, 8, 9, 10] r = corrcoef(x, y) >>> r array([[ 1., 0.72499943], [ 0.72499943, 1.]]) SciPy documentation Linear Regression from scipy import stats x = [1, 2, 3, 4, 5] y = [6, 7, 8, 9, 10] slope, intercept, r_value, p_value, std_err = stats.linregress(x,y) >>> slope, intercept (1.0, 5.0) SciPy documentation