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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.
Scaling of data: One of the properties of the tests is the scale of the data, which can be interval-based, ordinal or nominal. [3] Nominal scale is also known as categorical. [6] Interval scale is also known as numerical. [6] When categorical data has only two possibilities, it is called binary or dichotomous. [1]
The ordinal 1 is a multiplicative identity, α · 1 = 1 · α = α. Multiplication is associative, (α · β) · γ = α · (β · γ). Multiplication is strictly increasing and continuous in the right argument: (α < β and γ > 0) → γ·α < γ·β. Multiplication is not strictly increasing in the left argument, for example, 1 < 2 but 1 ...
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).
[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 a ranking. [2] It also differs from the interval scale and ratio scale by not having category widths that represent equal increments of the underlying attribute. [3]
Choose the right unit of measurement: "Many scales measure in ounces, pounds, and grams," notes Jardine. Check your recipe for the listed unit of measurement, then set your scale to match it.
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