The residual sum of squares refers to the sum of the squares of differences between the actual and the predicted values in a regression model. The calculator below finds the residual sum of squares on the basis of the predicted and actual values entered by the user.

Simply enter the predicted and actual response values in the calculator below to find the residual sum of squares.

**Predictor values:**

**Response values:**

**Residual Sum of Squares (SSE): 68.7878**

**Example:**

Suppose that the predictor values are: 6, 8, 11, 15

and, the actual observed values of the response variables are: 5, 10, 15, 12

Then the residual sum of squares can be found as,

RSS = (6-5)^{2} + (8-10)^{2} + (11-15)^{2} + (15-12)^{2} = 1 + 4+ 16 + 9 = 30