Total Sum of Squares (TSS)
Total sum of squares is used to denote the amount of variation in the dependent variable. The total sum of squares is the sum of the regression sum of squares and the residual sum of squares. It is calculated as:
TSS = RSS + SSR
Where the abbreviations have their usual meaning.
Residual Sum of Squares
Residual Sum of Squares is one of the types of sum of squares in regression which is used to measure the dispersion of the data points. The sum of squares can also be used to calculate the variance in the values of assets in the case of accounting. If the value of the sum of squares is higher, it represents a higher variance from the mean value and vice versa. The sum of squares is generally of 3 types i.e. Total Sum of Squares, Regressive or Regression Sum of Squares, and Residual Sum of Squares. In this article, we will study majorly the types of Residual Sum of Squares. Other than this we will also discuss both other types in bried as well.