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In statistics, the 68–95–99.7 rule, also known as the empirical rule, and sometimes abbreviated 3sr, is a shorthand used to remember the percentage of values that lie within an interval estimate in a normal distribution: approximately 68%, 95%, and 99.7% of the values lie within one, two, and three standard deviations of the mean, respectively.
Also, reliability is a property of the scores of a measure rather than the measure itself and are thus said to be sample dependent. Reliability estimates from one sample might differ from those of a second sample (beyond what might be expected due to sampling variations) if the second sample is drawn from a different population because the true ...
Often discussed in tandem with KR-20, is Kuder–Richardson Formula 21 (KR-21). [4] KR-21 is a simplified version of KR-20, which can be used when the difficulty of all items on the test are known to be equal. Like KR-20, KR-21 was first set forth as the twenty-first formula discussed in Kuder and Richardson's 1937 paper.
[3] [4] Seemingly unaware of McDonald's work, Jöreskog first analyzed a quantity equivalent to congeneric reliability in a paper the following year. [4] [5] Jöreskog defined congeneric reliability (now labeled ρ) with coordinate-free notation, [5] and three years later, Werts gave the modern, coordinatized formula for the same. [6]
Predicted reliability, ′, is estimated as: ′ = ′ + ′ where n is the number of "tests" combined (see below) and ′ is the reliability of the current "test". The formula predicts the reliability of a new test composed by replicating the current test n times (or, equivalently, creating a test with n parallel forms of the current exam).
The technique was developed in the Sandia Laboratories for the US Nuclear Regulatory Commission. [4] Its primary author is Swain, who developed the THERP methodology gradually over a lengthy period. [2] THERP relies on a large human reliability database that contains HEPs and is based upon both plant data and expert judgments. The technique was ...
A less-than-perfect test–retest reliability causes test–retest variability. Such variability can be caused by, for example, intra-individual variability and inter-observer variability. A measurement may be said to be repeatable when this variation is smaller than a predetermined acceptance criterion.
Lusser's law in systems engineering is a prediction of reliability.Named after engineer Robert Lusser, [1] and also known as Lusser's product law or the probability product law of series components, it states that the reliability of a series of components is equal to the product of the individual reliabilities of the components, if their failure modes are known to be statistically independent.