When two variables are correlated, it means that one is the cause of the other.

not so

Straight outta the book, " It is important to remember that correlation does not imply causation; in other words, just because two variables are highly correlated does not mean that one causes the other."

Actually, when two variables are correlated, it does not necessarily mean that one is the cause of the other. Correlation refers to the statistical relationship between two variables. It measures how changes in one variable are accompanied by changes in the other variable.

Correlation can be positive, negative, or zero. A positive correlation means that as one variable increases, the other variable also tends to increase. For example, there may be a positive correlation between studying time and exam scores, suggesting that more hours of studying are associated with higher test scores.

On the other hand, a negative correlation means that as one variable increases, the other variable tends to decrease. An example could be the relationship between hours spent watching TV and physical fitness. More hours watching TV might be associated with lower levels of physical fitness.

Zero correlation means there is no discernible relationship between the two variables. In this case, changes in one variable do not predict changes in the other.

It's important to note that correlation does not imply causation. Just because two variables are correlated does not mean that one variable is causing the other to change. Correlation only indicates that the variables are related in some statistical sense. To establish causation, you need to rely on additional evidence and research, such as well-designed experiments or strong theoretical explanations.