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When two variables are correlated, can the researcher be sure that one variable causes the other? If YES , why? If NO , why?

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Final answer:

Correlation does not imply causation. A researcher cannot assume that one variable causes another based solely on correlation. Other factors, known as confounding variables, may be responsible for the correlation.

Step-by-step explanation:

When two variables are correlated, it does not mean that one variable causes the other. Correlation does not imply causation. While a correlation between two variables can suggest a relationship, it is important to consider other factors, known as confounding variables, that may be responsible for the correlation.

For example, let's consider a study that found a positive correlation between the amount of ice cream consumed and the crime rate. Although there is a correlation, the true cause may be a confounding variable, such as temperature. Higher temperatures may lead to both increased ice cream consumption and higher crime rates, giving the appearance of a causal relationship between the two.

Therefore, a researcher cannot be sure that one variable causes the other based solely on a correlation. To establish causation, experimental studies with control over confounding variables are necessary.

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