Data Classification and Distribution

The objective of this paper is to explain the four main types of data. The classification of data by type is important for statistical analysis. In particular, data classification is useful for quantitative research in social science. 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.