"Correlation isn't Causation" - A causal explainer-AI causal argument analysis

Example

A user provides the title of a study suggesting a link between screen time and obesity. The tool examines the study's methodology to determine if it uses proper causal inference techniques like randomized controlled trials (RCTs) or instrumental variables.

Scenario

A researcher wants to verify if the claims made in a study about screen time causing obesity are valid. The tool analyzes the study to see if the methodology supports a causal claim or merely a correlation.

Example

Explaining why ice cream sales and drowning incidents are correlated due to a third factor (hot weather) rather than a direct causal relationship.

Scenario

A student is confused about why a spike in ice cream sales coincides with an increase in drowning incidents. The tool uses simple analogies to clarify that both are influenced by an external factor (temperature), not one causing the other.

Example

Guiding users through concepts like confounding variables, reverse causation, and how to interpret statistical results.

Scenario

A graduate student writing a thesis on public health seeks guidance on differentiating between causation and correlation in their data analysis. The tool provides educational resources and step-by-step explanations to help them understand and apply these concepts.