Evidence-Based Health Intelligence for India

Ever read a study claiming a "statistically significant" breakthrough, only to wonder what that actually means? Enter the p-value, the most famous—and misunderstood—metric in science. Think of a p-value as a reality check. It asks: If there is actually no real effect (the null hypothesis), how weird would it be to get my current data by pure chance? A tiny p-value (usually < 0.05) means your results would be extremely unlikely under those assumptions, giving you the green light to declare a "significant" finding. But beware the trap! A p-value doesn't measure how big or important an effect is, nor does it prove your theory is 100% true. It’s just one piece of the puzzle. To get the full picture, smart researchers combine p-values with effect sizes and confidence intervals. Want to see exactly how this works? Play with the interactive p-value explorer below to see how your test statistic shifts the probability!

A comprehensive data-driven retrospective on India's handling of the COVID-19 pandemic.

India faces a mounting mental health emergency — with over 150 million people affected but only 0.29 psychiatrists per 100,000 citizens.

Despite economic growth, one in three of the world's stunted children lives in India.

An analysis of the world's largest government-funded health insurance scheme.