Cause and Effect Questions in CLAT Logical Reasoning

Correlation means two events move together. Causation means one event actually produces the other.

CLAT LR often presents data trends and asks you to judge whether the author overstates causation from mere association.

A causal argument usually states an effect, names a cause, and assumes no stronger rival explanation exists.

If the author ignores timing, confounding variables, or selection bias, the argument becomes vulnerable.

Weaken by showing an alternative cause, reverse causality, or missing control conditions.

An option can also weaken by showing the alleged cause occurred without the effect, or the effect occurred without the alleged cause.

Strengthen by ruling out alternatives, showing temporal order, and presenting consistent results across relevant cases.

Options that tighten causal mechanism or reduce confounders are usually stronger than generic supportive statements.

In passage clusters, identify the exact causal claim first. Then mark what assumption the author makes about competing explanations.

This map helps you solve multiple question types in the same cluster without re-reading everything repeatedly.

Use previous-year CLAT-style passages and focus your review on why wrong options fail to affect the causal link.

Prep IQ Institute can help you master causation logic with passage-level mock reviews, assumption training, and elimination frameworks tailored to CLAT LR.