If a dataset has a significant positive correlation, can you definitively conclude that one variable causes the other?

No, you cannot definitively conclude that one variable causes the other simply because a dataset has a significant positive correlation. Correlation indicates a statistical relationship between two variables, meaning they tend to move together, either in the same direction (positive correlation) or in opposite directions (negative correlation). However, correlation does not imply causation. There are several possible reasons why two variables might be correlated without one causing the other. These include the presence of a confounding variable (a third variable influencing both), reverse causation (the apparent effect is actually the cause), or simply a coincidental relationship. Establishing causation requires more rigorous methods, such as controlled experiments or longitudinal studies that can rule out alternative explanations.