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Cronbach’s alpha is a measure of reliability but not validity. It can indicate whether responses are consistent between items (reliability), but it cannot determine whether the items measure the correct concept (validity).
Cronbach’s alpha is a measure of internal consistency, that is, how closely related a set of items are as a group. It is considered to be a measure of scale reliability. A “high” value for alpha does not imply that the measure is unidimensional.
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.
Cronbach’s alpha, α (or coefficient alpha), developed by Lee Cronbach in 1951, measures reliability, or internal consistency. “ Reliability ” is another name for consistency. Cronbach’s alpha tests to see if multiple-question Likert scale surveys are reliable.
Alpha is a commonly employed index of test reliability. Alpha is affected by the test length and dimensionality. Alpha as an index of reliability should follow the assumptions of the essentially tau-equivalent approach. A low alpha appears if these assumptions are not meet.
Cronbach's alpha is a measure used to assess the reliability, or internal consistency, of a set of scale or test items. In other words, the reliability of any given measurement refers to the extent to which it is a consistent measure of a concept, and Cronbach’s alpha is one way of measuring the strength of that consistency.
Cronbach’s alpha is used to measure the reliability – or internal consistency – of a set of scale items. It can be used, for example, to assess the internal consistency of items on a Likert scale questionnaire. In this tutorial we will show you how to calculate and interpret Cronbach’s alpha in SPSS.