ABSTRACT
In the midst of the Enlightenment, social scientists carved a space for the study of culture and societies in academia. With the development of social psychology and the rise of the interpretive movement, social scientists increased and expanded their focus on identity categories—sex, gender, race, ethnicity, class, education, and so forth. The most fundamental assumption of the general linear model is normality. Many statistical tests are said to be 'robust' enough to compensate for slight deviations from normality. In the early nineteenth century, mathematician Carl Friedrich Gauss introduced the notion of the normally distributed, or bell, curve. The Gaussian distribution is the underpinning of probability theory. The statistical output is an indicator of the likelihood that the two characteristics are related, given that all of the assumptions of the test are met. When analyzing statistical outputs, one must also be wary of possible spurious relationships.
