Probit models offer an alternative to logistic regression for modeling categorical dependent variables. It is the generalization of the Bernoulli distribution for a categorical random variable. Kant made a distinction between categorical and hypothetical imperatives. A histogram is an approximate representation of the distribution of numerical or categorical data. Statistics are generally collected on the assumption that religion is a categorical variable. Other plots are used for one categorical and one quantitative variables. In statistics, dummy variables represent a similar technique for representing categorical data. This extends mediation analysis to systems involving categorical variables in the presence of nonlinear interactions. The probability distribution associated with a random categorical variable is called a categorical distribution. Categorical, continuous, and discrete data can all form bimodal distributions . However, conflating the categorical and multinomial distributions can lead to problems. Kant defines the demands of moral law as "categorical imperatives". Distant' groupings contain words with broad categorical differences. QCA can be performed probabilistically or deterministically with observations of categorical variables. This third formulation makes it clear that the categorical imperative requires autonomy.