Correlation is not causation — Psychology, 14–17 years
Two things can change together without one causing the other. Psychology needs this distinction to judge claims about behaviour fairly.
What the pattern tells us
A correlation means that two measurements tend to vary together: when one is higher, the other often is too, or often is lower. It is a useful clue, but it does not by itself tell us what caused what, or whether a third factor affects both.
Why psychologists need the distinction
People naturally look for causes, especially when a neat pattern appears. Without this rule, an association could become a confident but false story: perhaps anxious students sleep less, but lack of sleep, workload, or another factor may be involved. Experiments and careful comparisons help test the cause.
A small example
Suppose a survey finds that students who use their phones more report more tiredness: the correlation is positive. Step 1: record both measures, such as hours and a tiredness score. Step 2: ask what else could explain both, such as late-night studying. Step 3: do not conclude that phone use alone caused tiredness without a stronger test.
The tempting arrow
The common mistake is to turn “A is linked with B” into “A causes B”. This feels reasonable because causes often do create patterns, and everyday decisions require quick guesses. The careful move is to label the result as an association until an experiment or other strong evidence rules out alternative explanations.
Reading claims in real life
You meet this idea in news reports, health advice, adverts and posts about school or sleep. When someone says that a habit “leads to” an outcome, ask whether the evidence is a correlation or a controlled comparison. That question does not reject the claim; it tells you how certain you are entitled to be.
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