If we know how successful a person is in college → we can predict what their SAT scores were (past tense because they took the SAT before they came to college). If we know a person’s SAT score → we can predict how successful they will be in college (this is what admissions offices do) or If SAT scores (A) are correlated to success in college (B), then… Some real examples (serious, silly, whatever): Why? Because the two are correlated: They fluctuate in a predictable pattern relative to each other. If all we know is the score of B → we can predict what the score will be on A. If all we know is the score of A → we can predict what the score will be on B or The stronger the correlation, the more accurate our predictions. We come across some situation of B without yet knowing A we can then predict what A will be because we know B and know there is a correlation between them. In other words, if we know that A and B are correlated we can use this knowledge when we come across some situation of A without yet knowing B we can then predict what B will be because we know A and know there is a correlation between them. When A and B correlate, we can use one to predict the other. And let’s say it’s a moderately-strong correlation. In vague terms, we measure two variables, one we call “A” and one we call “B.” Let’s say the calculations show that there is a correlation between A and B. Confusing? I only looked at it in the opposite direction. But wait, we can also predict what a person’s SAT score was if we know how successful that person now is in college. They let us make better predictions.įor example, if there is a correlation between SAT scores and success in college, we can predict who is most likely to be successful in college when we know people’s SAT scores. When we know there is a correlation, then we can use it to predict the value of one variable from the other. It tells us that two variables fluctuate in a predictable pattern relative to each other. Let’s back up a step: What is a correlation? A correlation is a statistical measurement. (Stop here for a moment and repeat that as a thought: you have discovered there IS a correlation, but you don’t know WHY the two things are correlated.) It means that when you know there is a correlation between two variables – which is worthwhile information in itself – you cannot know WHY the correlation exists.
Every class in psychology probably repeats the mantra, “correlation does not equal causation.” But what does it mean?
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