is a summary of how much of the variability of the data can be explained by a fitted regression model. It is calculated as
100 × (1 – (Residual m.s.)/(Total m.s.))
When expressed as a proportion rather than a percentage, this statistic is called the adjusted R2; it has the advantage over the statistic R2 (the squared coefficient of correlation, often used in regression) that it takes account of the number of parameters that have been fitted in the model.