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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.
The twelve equal scale is strictly proper as is any equal tempered scale because it has only one interval size for each number of steps Most tempered scales are proper too. As another example, the otonal harmonic fragment 5 ⁄ 4 , 6 ⁄ 4 , 7 ⁄ 4 , 8 ⁄ 4 is strictly proper, with the one step intervals varying in size from 8 ⁄ 7 to 5 ...
5 bits – the size of code points in the Baudot code, used in telex communication (a.k.a. pentad) 6 bits – the size of code points in Univac Fieldata, in IBM "BCD" format, and in Braille. Enough to uniquely identify one codon of genetic code. The size of code points in Base64; thus, often the entropy per character in a randomly-generated ...
Visual analogue scale (also called the Continuous rating scale and the graphic rating scale) – respondents rate items by placing a mark on a line. The line is usually labeled at each end. There are sometimes a series of numbers, called scale points, (say, from zero to 100) under the line.
Level of analysis is used in the social sciences to point to the location, size, or scale of a research target. It is distinct from unit of observation in that the former refers to a more or less integrated set of relationships while the latter refers to the distinct unit from which data have been or will be gathered.
Scales linearly with the scale parameter, and; Converges as the sample size grows. Various measures of statistical dispersion satisfy these. In order to make the statistic a consistent estimator for the scale parameter, one must in general multiply the statistic by a constant scale factor. This scale factor is defined as the theoretical value ...
The concept of data type is similar to the concept of level of measurement, but more specific. For example, count data requires a different distribution (e.g. a Poisson distribution or binomial distribution) than non-negative real-valued data require, but both fall under the same level of measurement (a ratio scale).
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.