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Measurement is a cornerstone of trade, science, technology and quantitative research in many disciplines. Historically, many measurement systems existed for the varied fields of human existence to facilitate comparisons in these fields.
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. Three common composite measures include:
In industrial instrumentation, accuracy is the measurement tolerance, or transmission of the instrument and defines the limits of the errors made when the instrument is used in normal operating conditions. [7] Ideally a measurement device is both accurate and precise, with measurements all close to and tightly clustered around the true value.
The level of measurement is the type of data that is measured. The word scale, including in academic literature, is sometimes used to refer to another composite measure , that of an index . Those concepts are however different.
Measurement uncertainty is a value associated with a measurement which expresses the spread of possible values associated with the measurand—a quantitative expression of the doubt existing in the measurement. [36] There are two components to the uncertainty of a measurement: the width of the uncertainty interval and the confidence level. [37]
A measurement system analysis (MSA) is a thorough assessment of a measurement process, and typically includes a specially designed experiment that seeks to identify the components of variation in that measurement process. Just as processes that produce a product may vary, the process of obtaining measurements and data may also have variation ...
Quantitative research is a research ... Views regarding the role of measurement in quantitative research are somewhat divergent. Measurement is often regarded as ...
The validity of a measurement tool (for example, a test in education) is the degree to which the tool measures what it claims to measure. [3] Validity is based on the strength of a collection of different types of evidence (e.g. face validity, construct validity, etc.) described in greater detail below.