what is the difference between the residual sum of squares and total sum of squares 
the total sum of squares tss measures how much variation there is in the observed data while the residual sum of squares measures the variation in the error between the observed data and modeled values in statistics the values for the residual sum of squares and the total sum of squares tss are oftentimes compared to each other can a residual sum of squares be zero the residual sum of squares can be zero the smaller the residual sum of squares the better your model fits your data the greater the residual sum of squares the poorer your model fits your data a value of zero means your model is a perfect fit the bottom lineresidual sum of squares quantifies the discrepancy between observed data points and the predictions made by a regression model calculated as the sum of the squared residuals minimizing rss is a fundamental objective in regression analysis as it represents the degree to which the model accurately captures the variability in the data 