Glossary

Coefficient of Determination

Coefficient of Determination:

In regression analysis, the coefficient of determination is a measure of goodness-of-fit (i.e. how well or tightly the data fit the estimated model). The coefficient is defined as the ratio of two sums of squares:

r² =

SSR

SST

where SSR is the sum of squares due to regression, SST is the total sum of squares. By “sum of squares” we mean the sum of squared deviations between actual values and the mean (SST), or between predicted values and the mean (SSR). The coefficient of determination takes on values between 0 and 1, with values closer to 1 implying a better fit.

Browse Other Glossary Entries

Test Yourself

Planning on taking an introductory statistics course, but not sure if you need to start at the beginning? Review the course description for each of our introductory statistics courses and estimate which best matches your level, then take the self test for that course. If you get all or almost all the questions correct, move on and take the next test.