We will speak of causality, if there is an interdependence of cause and effect between two variables. Correlation can indicate causal relationships. A person who is a heavy smoker (variable X) has a higher risk of suffering from lung cancer (variable Y). Keep in mind though, that a correlation in itself does not prove causality. Two variables can have a statistical relationship without there actually being a mutual influence. In this context we also speak of spurious correlation.
Please note that the definitions in our statistics encyclopedia are simplified explanations of terms. Our goal is to make the definitions accessible for a broad audience; thus it is possible that some definitions do not adhere entirely to scientific standards.