The problem with making this observation is that you may fail to consider other factors or variables that could cause the correlation. When a clear relationship exists between variables, it can be easy to say that a cause-and-effect relationship is present.
Correlation versus causation is an important consideration since the presence of a correlation between two variables doesn’t mean one causes the other. The concept of correlation versus causation strives to determine if two events are simply related to each other or if one caused the other to happen. However, this isn’t always the case, making it important to be able to distinguish between correlation and causation. In a situation where two variables have a similar response to an event, you may assume that one event caused the other or that the two variables are somehow directly connected. Correlation only identifies that there is a relationship between two events or outcomes. Causation indicates that one event causes another.
However, the two terms are not interchangeable and have significant differences. In analytics, correlation and causation both describe relationships between variables.