9.3. Measures of Variation

Once a regression model has been fit to a set of data, three measures of variation determine how much of the variation in the dependent variable Y can be explained by variation in the independent variable X. The first measure, the total sum of squares (SST), is a measure of variation of the Y values around their mean, . In a regression analysis, the total variation or total sum of squares is subdivided into explained variation or regression sum of squares (SSR), that which is due to the relationship between X and Y, and unexplained variation or error sum of squares (SSE), that which is due to factors other than the relationship ...

Get Statistics for Six Sigma Green Belts with Minitab and JMP now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.