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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.
For example, a scaling technique might involve estimating individuals' levels of extraversion, or the perceived quality of products. Certain methods of scaling permit estimation of magnitudes on a continuum, while other methods provide only for relative ordering of the entities. The level of measurement is the type of data that is measured.
It is when a Likert scale is symmetric and equidistant that it will behave more like an interval-level measurement. So while a Likert scale is indeed ordinal, if well presented it may nevertheless approximate an interval-level measurement. This can be beneficial since, if it was treated just as an ordinal scale, then some valuable information ...
A rating scale is a set of categories designed to obtain information about a quantitative or a qualitative attribute. In the social sciences, particularly psychology, common examples are the Likert response scale and 0-10 rating scales, where a person selects the number that reflecting the perceived quality of a product.
It is a measure of rank correlation: the similarity of the orderings of the data when ranked by each of the quantities. It is named after Maurice Kendall, who developed it in 1938, [1] though Gustav Fechner had proposed a similar measure in the context of time series in 1897. [2]
The response categories represent an ordinal level of measurement.Ordinal level data, however, varies in terms of how closely it approximates interval level data. By using a numerical continuum as the response key instead of sentiments that reflect intensity of agreement, respondents may be able to quantify their responses in more equal units.
(For example, a respondent's scale score of 2 implies that that respondent responded positively to questions 1 and 2 and negatively to questions 3, 4, and 5.) Guttman scale, if supported by data, is useful for efficiently assessing subjects (respondents, testees or any collection of investigated objects) on a one-dimensional scale with respect ...