pseudocyesis is a false correlation between two variables caused by a third variable.
a false correlation between two variables caused by a third variable?
pseudocyesis
the concept of correlation is particularly noteworthy for the potential confusion it can cause. statistical analysis of a data set often reveals that two variables (properties) of the population under consideration tend to vary together, as if they were connected. for example, a study of annual income that also looks at age of death might find that poor people tend to have shorter lives than affluent people. the two variables are said to be correlated; however, they may or may not be the cause of one another. the correlation phenomena could be caused by a third, previously unconsidered phenomenon, called a lurking variable or confounding variable. for this reason, there is no way to immediately infer the existence of a causal relationship between the two variables. (see correlation does not imply causation.)
statistics
when two variables are related, or correlated, one can make predictions for these two variables. however, it is important to note that this does not mean causality. at this point, it is not possible to determine a causal relationship between the two variables; correlation does not imply causality. however, correlation evidence is significant because it can help identify potential causes of behavior. path analysis is a statistical technique that can be used with correlational data. this involves the identification of mediator and moderator variables. a mediator variable is used to explain the correlation between two variables. a moderator variable affects the direction or strength of the correlation between two variables. a spurious relationship is a relationship in which the relation between two variables can be explained by a third variable.
survey (human research)