Data are defined as a quantitative measurement of qualitative fact. Data are classified into three types: quantitative, ordinal and nominal. Quantitative data are those that may be subject to mathematical operations: addition, subtraction, multiplication and division. Ordinal data are those that rank the values in a data set in an ascending order (from low to high) or from descending order (from high to low). Nominal data are those numbers or designation of value that is used for the purpose of identification. Nominal data cannot be subjected to mathematical operations. In addition to types, the data may also be classified according to their probability nature: (i) discrete data for discrete probability and (ii) continuous data for continuous probability.
A distribution is the fraction of individual events in relations to the whole number of observation. Adding all the individual events, the sum of the distribution is 1.0, i.e. each event is a proportion to the whole where the whole (of whatever is being observed) is 100% or simply 1.0.
A probability distribution is the probability of a subset of the possible outcome in relations to the entire observation. There are two types of probability based on the nature of the data: (i) discrete data produces discrete probability, and (ii) continuous data produces continuous probability function. Graphically, discrete probability produces a picture of a histogram where each data point stands alone and not connected to any other data point. Graphically, a continuous data set produces a continuous line or curve. The distribution is cumulative.