Mean difference is divided by this quantity to calculate Cohen's d, which measures effect size.
Mean difference is divided by this quantity to calculate Cohen's d, which measures effect size. This quantity equals the square root of the quantity number of trials times probability of success times probability of failure for a binomial distribution. It is squared in the denominator of Chebyshev's inequality, which guarantees at least a certain number of values close to the mean of a distribution. This quantity is multiplied by the square root of two pi in a denominator to normalize the (*) Gaussian distribution. The difference between a score and the mean is divided by this quantity to calculate z-scores. It equals the square root of the expected value of the quantity score minus mean, quantity squared. For 10 points, name this square root of variance.
Mean difference is divided by this quantity to calculate Cohen's d, which measures effect size.
standard deviation