McGraw and Wong (1992) have described a very appealing index of effect size that requires no prior knowledge of statistics to understand, which they termed CL, the common language effect size indicator. CL is the probability that a score randomly sampled from one distribution will be larger than a randomly sampled score from a second distribution. McGraw and Wong describe how to compute CL from the means and standard deviations of two groups, using tables of normal curve probability values. The program described herein computes CL without lookup tables but also permits the user to compute CL from Cohen's d, from a t test for independent groups, or from point-biserial r, the correlation between a dichotomous and a continuous variable. A table giving CL for various values of d is also provided, as are the equations for converting t and r to d.