Why use correlations?

Why use correlations?

• A. Simple and informative
• B. To prove causation
• C. To replace regression
• D. To measure central tendency

Answer: (A)

Correlations give a simple, informative summary of how two variables relate: they indicate whether the variables move together (positive), move in opposite directions (negative), and how strong that relationship is. This quick snapshot is useful when you’re exploring data to decide what relationships might be worth studying further or modeling more formally. But correlation does not establish cause and effect, so it can’t prove that one variable influences the other. It also doesn’t replace regression, which provides an equation to describe how one variable changes with another and supports prediction under certain assumptions. And correlation isn’t about a single variable’s typical value—that’s the realm of measures of central tendency like the mean or median.

Correlations give a simple, informative summary of how two variables relate: they indicate whether the variables move together (positive), move in opposite directions (negative), and how strong that relationship is. This quick snapshot is useful when you’re exploring data to decide what relationships might be worth studying further or modeling more formally. But correlation does not establish cause and effect, so it can’t prove that one variable influences the other. It also doesn’t replace regression, which provides an equation to describe how one variable changes with another and supports prediction under certain assumptions. And correlation isn’t about a single variable’s typical value—that’s the realm of measures of central tendency like the mean or median.