Contingency analysis is used to detect and investigate relationships between nominally scaled variables. Typical examples are the investigation of associations between income class, profession or gender and consumer behavior, or the examination of whether the level of education or the family background (social class) is associated with the membership in a particular political party. Questions arising in this context may include: Is there a significant association between the variables? Is it possible to make a statement about the strength or even the direction of the association? This chapter describes contingency analysis for the simple 2 × 2 case as well as for larger cross tables. Furthermore, the role of confounding variables is discussed.