a false correlation between two variables caused by a third variable
lurking variable
title: Correlation does not imply causation text: and vice versa. The third-cause fallacy (also known as "ignoring a common cause" or "questionable cause") is a logical fallacy where a spurious relationship is confused for causation. It asserts that X causes Y when, in reality, X and Y are both caused by Z. It is a variation on the "post hoc ergo propter hoc" fallacy and a member of the questionable cause group of fallacies. All of these examples deal with a lurking variable, which is simply a hidden third variable that affects both causes of the correlation. A difficulty often also arises where the third factor, though title: Illusory correlation text: Illusory correlation In psychology, illusory correlation is the phenomenon of perceiving a relationship between variables (typically people, events, or behaviors) even when no such relationship exists. A false association may be formed because rare or novel occurrences are more salient and therefore tend to capture one's attention. This phenomenon is one way stereotypes form and endure. found that stereotypes can lead people to expect certain groups and traits to fit together, and then to overestimate the frequency with which these correlations actually occur. "Illusory correlation" was originally coined by Chapman and Chapman (1967) to describe people's tendencies to overestimate relationships title: Negative relationship text: Negative relationship In statistics, there is a negative relationship or inverse relationship between two variables if higher values of one variable tend to be associated with lower values of the other. A negative relationship between two variables usually implies that the correlation between them is negative, or — what is in some contexts equivalent — that the slope in a corresponding graph is negative. A negative correlation between variables is also called anticorrelation or inverse correlation. Negative correlation can be seen geometrically when two normalized random vectors are viewed as points on a sphere, and the correlation between them is title: Correlation does not imply causation text: Correlation does not imply causation In statistics, many statistical tests calculate correlations between variables and when two variables are found to be correlated, it is tempting to assume that this shows that one variable causes the other. That "correlation proves causation" is considered a questionable cause logical fallacy when two events occurring together are taken to have established a cause-and-effect relationship. This fallacy is also known as cum hoc ergo propter hoc, Latin for "with this, therefore because of this", and "false cause". A similar fallacy, that an event that followed another was necessarily a consequence of the first event, title: Spurious relationship text: Spurious relationship In statistics, a spurious relationship or spurious correlation is a mathematical relationship in which two or more events or variables are not causally related to each other, yet it may be wrongly inferred that they are, due to either coincidence or the presence of a certain third, unseen factor (referred to as a "common response variable", "confounding factor", or "lurking variable"). A well-known case of a spurious relationship can be found in the time-series literature, where a spurious regression is a regression that provides misleading statistical evidence of a linear relationship between independent non-stationary variables. In fact, the