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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.
In comparison, variables with unordered scales are nominal variables. [1] Visual difference between nominal and ordinal data (w/examples), the two scales of categorical data [2] A nominal variable, or nominal group, is a group of objects or ideas collectively grouped by a particular qualitative characteristic. [3]
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]
Scales constructed should be representative of the construct that it intends to measure. [6] It is possible that something similar to the scale a person intends to create will already exist, so including those scale(s) and possible dependent variables in one's survey may increase validity of one's scale.
The psychophysicist Stanley Smith Stevens defined nominal, ordinal, interval, and ratio scales. Nominal measurements do not have meaningful rank order among values, and permit any one-to-one transformation.
In manufacturing, a nominal size or trade size is a size "in name only" used for identification. [1] The nominal size may not match any dimension of the product, but within the domain of that product the nominal size may correspond to a large number of highly standardized dimensions and tolerances.
Composite measure in statistics and research design refer to composite measures of variables, i.e. measurements based on multiple data items. [1]An example of a composite measure is an IQ test, which gives a single score based on a series of responses to various questions.
Such classification is usually done on a nominal scale. [1] Typologies are used in both qualitative and quantitative research. An example of a typology would be classification such as by age and health: young-healthy, young-sick, old-healthy, old-sick.