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Comparison of the various grading methods in a normal distribution, including: standard deviations, cumulative percentages, percentile equivalents, z-scores, T-scores. In statistics, the standard score is the number of standard deviations by which the value of a raw score (i.e., an observed value or data point) is above or below the mean value of what is being observed or measured.
When the score distribution is approximately normally distributed, sten scores can be calculated by a linear transformation: (1) the scores are first standardized; (2) then multiplied by the desired standard deviation of 2; and finally, (3) the desired mean of 5.5 is added. The resulting decimal value may be used as-is or rounded to an integer.
The mean and the standard deviation of a set of data are descriptive statistics usually reported together. In a certain sense, the standard deviation is a "natural" measure of statistical dispersion if the center of the data is measured about the mean. This is because the standard deviation from the mean is smaller than from any other point.
The DAS-II yields a General Conceptual Ability (GCA) score scaled like an IQ score with the mean standard score set at 100 and 15 standard score points for each standard deviation up or down from the mean. The lowest possible GCA score on DAS–II is 30, and the highest is 170. [52]
Stanine (STAndard NINE) is a method of scaling test scores on a nine-point standard scale with a mean of five and a standard deviation of two.. Some web sources attribute stanines to the U.S. Army Air Forces during World War II.
A raw score is a score without any sort of adjustment or transformation, such as the simple number of questions answered correctly. A scaled score is the result of some transformation(s) applied to the raw score, such as in relative grading. The purpose of scaled scores is to report scores for all examinees on a consistent scale.
In another usage in statistics, normalization refers to the creation of shifted and scaled versions of statistics, where the intention is that these normalized values allow the comparison of corresponding normalized values for different datasets in a way that eliminates the effects of certain gross influences, as in an anomaly time series. Some ...
The reason for the choice of the number 21.06 is to bring about the following result: If the scores are normally distributed (i.e. they follow the "bell-shaped curve") then the normal equivalent score is 99 if the percentile rank of the raw score is 99; the normal equivalent score is 50 if the percentile rank of the raw score is 50;