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In statistics and research, internal consistency is typically a measure based on the correlations between different items on the same test (or the same subscale on a larger test). It measures whether several items that propose to measure the same general construct produce similar scores. For example, if a respondent expressed agreement with the ...
Cronbach's alpha (Cronbach's ), also known as tau-equivalent reliability ( ) or coefficient alpha (coefficient ), is a reliability coefficient and a measure of the internal consistency of tests and measures. [1][2][3] It was named after the American psychologist Lee Cronbach. Numerous studies warn against using Cronbach's alpha unconditionally.
Administering one form of the test to a group of individuals. At some later time, administering an alternate form of the same test to the same group of people. Correlating scores on form A with scores on form B. The correlation between scores on the two alternate forms is used to estimate the reliability of the test.
Kuder–Richardson formulas. In psychometrics, the Kuder–Richardson formulas, first published in 1937, are a measure of internal consistency reliability for measures with dichotomous choices. They were developed by Kuder and Richardson.
Validity is the main extent to which a concept, conclusion, or measurement is well-founded and likely corresponds accurately to the real world. [1][2] The word "valid" is derived from the Latin validus, meaning strong. The validity of a measurement tool (for example, a test in education) is the degree to which the tool measures what it claims ...
In statistics, inter-rater reliability (also called by various similar names, such as inter-rater agreement, inter-rater concordance, inter-observer reliability, inter-coder reliability, and so on) is the degree of agreement among independent observers who rate, code, or assess the same phenomenon. Assessment tools that rely on ratings must ...
Data quality refers to the state of qualitative or quantitative pieces of information. There are many definitions of data quality, but data is generally considered high quality if it is "fit for [its] intended uses in operations, decision making and planning ". [1][2][3] Moreover, data is deemed of high quality if it correctly represents the ...
The modern models reorganize classical "validities" into either "aspects" of validity [3] or "types" of validity-supporting evidence [1] Test validity is often confused with reliability, which refers to the consistency of a measure. Adequate reliability is a prerequisite of validity, but a high reliability does not in any way guarantee that a ...