The Frequentist Approach Observe data. Assume the data were generated randomly, e.g. by nature, by designing a survey, etc. Make assumptions on the generating process, e.g. i.i.d., Gaussian, etc. Associate the generating process to some object of interest, e.g. a parameter, a density, etc. Assuming that the object is unknown but fixed, try to find it, e.g. estimate it, test a hypothesis about it, etc. The Bayesian Approach Observe data....

This list is not exhaustive. For example, lists multiple distance and similarity measures for different kinds of data: numerical (12), boolean (8), string (5), images & color (2), geospatial & temporal (4), and general & mixed (1).
Nominal variables are variables that have two or more categories, but which do not have an intrinsic order. Dichotomous variables are nominal variables which have only two categories.
Dichotomous attributes (e.g. yes-or-no) are distinct from binary attributes (present vs....