hypothesis-test

T-test in Pandas

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it depends what sort of t-test you want to do (one sided or two sided dependent or independent) but it should be as simple as: from scipy.stats import ttest_ind cat1 = my_data[my_data[‘Category’]==’cat1′] cat2 = my_data[my_data[‘Category’]==’cat2′] ttest_ind(cat1[‘values’], cat2[‘values’]) >>> (1.4927289925706944, 0.16970867501294376) it returns a tuple with the t-statistic & the p-value see here for other t-tests … Read more

Find p-value (significance) in scikit-learn LinearRegression

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This is kind of overkill but let’s give it a go. First lets use statsmodel to find out what the p-values should be import pandas as pd import numpy as np from sklearn import datasets, linear_model from sklearn.linear_model import LinearRegression import statsmodels.api as sm from scipy import stats diabetes = datasets.load_diabetes() X = diabetes.data y … Read more