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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. [1][2] This framework of distinguishing ...
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 ...
Informally, in frequentist statistics, a confidence interval (CI) is an interval which is expected to typically contain the parameter being estimated. More specifically, given a confidence level (95% and 99% are typical values), a CI is a random interval which contains the parameter being estimated % of the time. [1][2] The confidence level ...
In statistics and applications of statistics, normalization can have a range of meanings. [1] In the simplest cases, normalization of ratings means adjusting values measured on different scales to a notionally common scale, often prior to averaging. In more complicated cases, normalization may refer to more sophisticated adjustments where the ...
Statistics (from German: Statistik, orig. "description of a state, a country") [1][2] is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. [3][4][5] In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a ...
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 ...
Accuracy is also used as a statistical measure of how well a binary classification test correctly identifies or excludes a condition. That is, the accuracy is the proportion of correct predictions (both true positives and true negatives) among the total number of cases examined. [10]
Measurement uncertainty. In metrology, measurement uncertainty is the expression of the statistical dispersion of the values attributed to a quantity measured on an interval or ratio scale. All measurements are subject to uncertainty and a measurement result is complete only when it is accompanied by a statement of the associated uncertainty ...