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Level of measurement or scale of measure is a classification that describes the nature of information within the values assigned to variables. [1] Psychologist Stanley Smith Stevens developed the best-known classification with four levels, or scales, of measurement: nominal , ordinal , interval , and ratio .
Ordinal data is a categorical, statistical data type where the variables have natural, ordered categories and the distances between the categories are not known. [ 1 ]: 2 These data exist on an ordinal scale, one of four levels of measurement described by S. S. Stevens in 1946. The ordinal scale is distinguished from the nominal scale by having ...
e. In statistics, ordinal regression, also called ordinal classification, is a type of regression analysis used for predicting an ordinal variable, i.e. a variable whose value exists on an arbitrary scale where only the relative ordering between different values is significant. It can be considered an intermediate problem between regression and ...
Kendall rank correlation coefficient. In statistics, the Kendall rank correlation coefficient, commonly referred to as Kendall's τ coefficient (after the Greek letter τ, tau), is a statistic used to measure the ordinal association between two measured quantities. A τ test is a non-parametric hypothesis test for statistical dependence based ...
Univariate is a term commonly used in statistics to describe a type of data which consists of observations on only a single characteristic or attribute. A simple example of univariate data would be the salaries of workers in industry. [1] Like all the other data, univariate data can be visualized using graphs, images or other analysis tools ...
Statistical data type. In statistics, groups of individual data points may be classified as belonging to any of various statistical data types, e.g. categorical ("red", "blue", "green"), real number (1.68, −5, 1.7 × 10+6), odd number (1,3,5) etc. The data type is a fundamental component of the semantic content of the variable, and controls ...
Confirmatory factor analysis. In statistics, confirmatory factor analysis (CFA) is a special form of factor analysis, most commonly used in social science research. [1] It is used to test whether measures of a construct are consistent with a researcher's understanding of the nature of that construct (or factor).
Definition: Guttman scale is a data set for which there exists an ordinal variable, X, with a finite number m of categories, say, 1,..., m with m ≥ max j (kj) and a permutation of subjects' profiles such that each variable in the data set is a simple function of X. Despite its seeming elegance and appeal for exploratory research, this ...