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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 .
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.
In practice, then, it is common for trainers to get stuck in Levels 1 and 2 and never proceed to Levels 3 and 4, where the most useful data exist. Today, Kirkpatrick-certified facilitators stress "starting with the end in mind," essentially beginning with Level 4 and moving backward in order to better establish the desired outcome before ever ...
Level 3 is what is usually used to measure how many people in the world know a given language. A person at this level is described as follows: able to speak the language with sufficient structural accuracy and vocabulary to participate effectively in most conversations on practical, social, and professional topics
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).
The process will determine the measurement value and uncertainty of the device that is being calibrated (the comparator) and create a traceability link to the measurement standard. [34] The four primary reasons for calibrations are to provide traceability, to ensure that the instrument (or standard) is consistent with other measurements, to ...
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.
The standard also provides a schema for Sampling Features. Observations commonly involve sampling of the ultimate feature of interest. Specific sampling features, such as station, specimen, transect, section, are used in many application domains, and common processing and visualization tools are used.