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Mean square error or MSE is frequently requested by journals as a companion statistic for ANOVA and, especially, t-tests. MSE is the average intra-group variance. MSE is outputted in ANOVA tables but can be computed using a weighted average of the group variances. Fo G groups with the i-th an SD, $$SD_text{i}$$ and sample size $$N_text{i}$$, MSE = $$\sum$$ over i [$$(N(i)-1) SD(i)2 ]/ [($$\sum$$ over i)N(i)) - G ] $$ which equals ($$\sum$$ over i $$SD(i)2 )/G $$ in the special case of equal group sizes. MSE is also useful for computing Cohen's d effect size, the number of standard deviations between a pair of group means, because d = (difference in a pair of group means) divided by the square root of the MSE In EXCEL, suppose we have two groups (A and B ) in cells A1:A100 and B1:B100 respectively, Cohen's d can then be computed using COHENSD =(SQRT(((COUNT(A1:A100)-1)+(COUNT(B1:B100)-1)))*(AVERAGE(A1:A100)-AVERAGE(B1:B100)))/(SQRT((COUNT(A1:A100)-1)*POWER(STDEV(A1:A100),2)+(COUNT(B1:B100)-1)*POWER(STDEV(B1:B100),2))) and the mean square error in EXCEL is computed by MSE = ((COUNT(A1:A100)-1)*POWER(STDEV(A1:A100),2)+(COUNT(B1:B100)-1)*POWER(STDEV(B1:B100),2))/((COUNT(A1:A100)-1)+(COUNT(B1:B100)-1))