Computer Science 1044
Introduction to C Programming

CS1044: Krider Curve


The Krider Curve was developed by Dr. Daniel W. Krider, Professor of Mathematics, Concord College, Athens, WV. The curve coerces grades into forming a distribution which more closely resembles a Normal Distribution. This is a partial solution to the problem of class grades tending to be skewed toward the lower values. The Krider Curve forces symmetrical clustering about the mean (property of central tendency) and smaller variance within the scores (less dispersion).


Mathematical Derivation

Given the following:

The following formula is applied to each individual student grade:

This is equivalent to averaging two X values with one grade of a 100. The lower scores receive a larger curve than the upper scores. An appropriate action when one considers that poorer students require more help. The curve ensures that a student will never surpass another student who scores higher.

Alpha can be set to achieve a desired class mean.

Where:

The formula for deriving alpha's value for a desired mean:


Author: N. Dwight Barnette
Curator: Computer Science Dept : VA TECH © Copyright 2001
Last Updated: 1/11/01