Select Regression and click OK. 3. Thus Σ i (y i - ybar) 2 = Σ i (y i - yhat i) 2 + Σ i (yhat i - ybar) 2 On the Data tab, in the Analysis group, click Data Analysis. Total sums of squares = Residual (or error) sum of squares + Regression (or explained) sum of squares.
Select the X Range (B1:C8). Note: can't find the Data Analysis button?

This is the predictor variable (also called dependent variable). returns a column array with SSRow, SSCol, SSInt and SSW for a two factor ANOVA for the data in R1 using a regression model; if r > 0 then R1 is assumed to be in Excel Anova format (with headings) with r rows per sample, while if r = 0 or is omitted then R1 is assumed to be in standard format (w/o headings) Note the following about the regression coefficients: The intercept b0 = mean of the Flavor 3 group = 14. The ANOVA (analysis of variance) table splits the sum of squares into its components.
4. Click here to... 2. Regression 1. Select the Y Range (A1:A8).