Random errors are the chance factors that can distort the true score and are inversely proportional to the degree of reliability. Measurement error can be random or non-random. Reliability is majorly an empirical issue concentrated on the performance of an empirical measure. Reliability = True score/ (True score + Errors) In theory, reliability refers to the true score variance to the observed score variance. Four major ways of assessing reliability are test-retest, parallel test, internal consistency, and inter-rater reliability. Reliability, thus, is a matter of degree. This consistency is what we refer to as reliability. At the same time, we can and should expect consistent results on repeated measurement from a good experiment, test, or instrument. Even repeated measures of the same characteristics for the same individual might not duplicate themselves. However, the measurement of any phenomenon invariably contains a certain amount of chance error. Reliability, fundamentally, concerns the extent to which a measure, an experiment, or test yields the same results on repeated trials.
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