The usual results for linear combinations of independent random variables mean that the variance of a contrast is equal to the weighted sum of the variances. If two contrasts are orthogonal, estimates created by using such contrasts will be uncorrelated. If orthogonal contrasts are available, it is possible to summarize the results of a statistical analysis in the form of a simple analysis of variance table, in such a way that it contains the results for different test statistics relating to different contrasts, each of which are statistically independent. Linear contrasts can be easily converted into sums of squares. SScontrast = formula_9, with 1 degree of freedom, where "n" represents the number of observations per group. If the contrasts are orthogonal, the sum of the SScontrasts = SStreatment. Testing the significance of a contrast requires the computation of SScontrast. A recent development in statistical analysis is the standardized mean of a contrast variable. This makes a comparison between the size of the differences between groups, as measured by a contrast and the accuracy with which that contrast can be measured by a given study or experiment.