Reliability (statistics)

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Reliability (statistics)

Reliability in statistics refers to the consistency of a set of measurements or measuring instrument, often used to describe a test. This concept is related to the fields of psychometrics, measurement theory, and quantitative research.

Pronunciation

Reliability: /rɪˌlaɪəˈbɪlɪti/

Etymology

The term "reliability" originates from the Latin word "reliabilis", which means "something that can be relied upon".

Definition

In statistics, reliability is the overall consistency of a measure. A measure is said to have a high reliability if it produces similar results under consistent conditions. It is important to note that reliability does not imply validity. That is, a reliable measure that is measuring something consistently is not necessarily measuring what it is intended to measure.

Types of Reliability

There are several types of reliability, including:

  • Test-retest reliability: This refers to the stability of a test over time. A test has test-retest reliability if it measures the same thing consistently on different occasions.
  • Parallel forms reliability: This refers to the equivalence of different forms of the same test. A test has parallel forms reliability if different versions of the test produce similar results.
  • Internal consistency reliability: This refers to the consistency of results across items within a test. A test has internal consistency reliability if all items measure the same construct and produce similar scores.

Related Terms

  • Validity: This refers to the extent to which a test measures what it claims to measure. It is possible for a test to be reliable, but not valid.
  • Measurement error: This refers to the difference between the observed value and the true value. Measurement error can affect the reliability of a test.
  • Coefficient alpha: This is a measure of internal consistency reliability. It is often used in psychometrics to estimate the reliability of a test.

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