Blog
Developments in automated analysis, new software, research commentary and notes on where the field is going.
How to compare two proportions with a z-test in Statsmodels (with Code)
Pass two success counts and their corresponding trial counts to proportions_ztest with value=0 to test equal proportions in independent groups.
How to calculate a Wilson interval for a binomial proportion in Statsmodels (with Code)
Call proportion_confint with the observed success count, total trial count and method="wilson" to calculate a Wilson score interval for one binomial proportion.
How to adjust p-values with the Benjamini-Hochberg method in Statsmodels (with Code)
Pass the complete planned family of p-values to multipletests with method="fdr_bh" to obtain Benjamini-Hochberg adjusted p-values and rejection decisions.
How to bootstrap a confidence interval for the median in SciPy (with Code)
Call scipy.stats.bootstrap with np.median, a one-element data tuple and a recorded random generator seed to estimate a median confidence interval.
How to run a permutation test for a difference in means in SciPy (with Code)
Pass a difference-of-means function to scipy.stats.permutation_test with permutation_type="independent" for two exchangeable independent samples.
How to test variance homogeneity with the Levene test in SciPy (with Code)
Call scipy.stats.levene with center="median" to compare the spreads of independent groups using median-centered absolute deviations.
B.Tech in AI and Machine Learning from BITS Pilani WILP: The 2026 Complete Guide
BITS Pilani WILP B.Tech in AI & ML is a 4-year online degree for working professionals. Cost: ~INR 50–55K/semester (~INR 4–4.4L total). Best for professionals without a CS background who need a recognised undergraduate AI/ML credential for career transitions. Slower and more expensive than bootcamps but provides a degree.
How to calculate a Spearman rank correlation in SciPy (with Code)
Use scipy.stats.spearmanr to calculate the correlation of average ranks, keeping each pair of observations aligned.
How to calculate a Pearson correlation and confidence interval in SciPy (with Code)
Call scipy.stats.pearsonr on matched numeric observations, then use its confidence_interval method for a Fisher-transformed interval.
How to run Fisher’s exact test in SciPy (with Code)
Call scipy.stats.fisher_exact with a two-by-two table of nonnegative integer counts and an explicit alternative.