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In educational statistics, a normal curve equivalent (NCE), developed for the United States Department of Education by the RMC Research Corporation, [1] is a way of normalizing scores received on a test into a 0-100 scale similar to a percentile rank, but preserving the valuable equal-interval properties of a z-score.
"The Flesch–Kincaid" (F–K) reading grade level was developed under contract to the U.S. Navy in 1975 by J. Peter Kincaid and his team. [1] Related U.S. Navy research directed by Kincaid delved into high-tech education (for example, the electronic authoring and delivery of technical information), [2] usefulness of the Flesch–Kincaid readability formula, [3] computer aids for editing tests ...
The automated readability index (ARI) is a readability test for English texts, designed to gauge the understandability of a text. Like the Flesch–Kincaid grade level, Gunning fog index, SMOG index, Fry readability formula, and Coleman–Liau index, it produces an approximate representation of the US grade level needed to comprehend the text.
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.
Similarly, a grade point average of 3.0 on a 4.0 scale would indicate that the student is within the top 20 % of the class. Grading curves serve to attach additional significance to these figures, and the specific distribution employed may vary between academic institutions.
The figure illustrates the percentile rank computation and shows how the 0.5 × F term in the formula ensures that the percentile rank reflects a percentage of scores less than the specified score. For example, for the 10 scores shown in the figure, 60% of them are below a score of 4 (five less than 4 and half of the two equal to 4) and 95% are ...