What is the difference between causal inference and correlational studies?

What is the difference between causal inference and correlational studies?

Causal inference aims to determine if one event causes another, while correlational studies only identify relationships.

Can you give me an example of each?

Sure! A causal inference example is a study showing that smoking causes lung cancer. A correlational study might show that ice cream sales and drowning incidents increase in summer, but one doesn't cause the other.

How do researchers establish causality?

Researchers use methods like randomized controlled trials, longitudinal studies, and statistical techniques to establish causality.

What are some common pitfalls in correlational studies?

Common pitfalls include confusing correlation with causation, overlooking confounding variables, and not considering the direction of the relationship.

Why is understanding this difference important?

Understanding the difference helps in making informed decisions based on research findings and avoiding misleading conclusions.