Causal Inference: An Intuitive Introduction

Understand the Foundations of Causal Inference without any complex math

In the last article, we discussed The Traps of Blindly Trusting Data: Simpson’s Paradox

This article aims to understand the cause and effect within scenarios and uncover causal relationships in observational studies using Causal Inference.

Consider a Scenario: What will be the effect of treating a disease with a new medicine, A, and will it be effective at improving patient’s health?

Answering the question above involves causal analysis, comparing how patients respond to the medication. We want to understand what would have happened if they had not taken the medication instead. This is where causal inference comes in.

Causal inference is a fundamental concept in statistics, epidemiology, economics, and other fields concerned with understanding cause-and-effect relationships. It involves making inferences about the causal effect of an intervention, treatment, or exposure on an outcome of interest.

Causal inference is the basis for scientific inquiry. Any claim regarding cause and effect relies upon certain…