RSS is the aggregated squared residuals of all of the data. This is shown with the formula:

$RSS = e_1^2 + e_2^2 + ... + e_n^2$ or alternatively, $RSS=\sum_{i=1}^n (y_i-\hat{\beta}_0-\hat{\beta}_1x_i)^2$, where $\hat{\beta}_0, \hat{\beta}_1$ are the model parameters.

The RSS should be a smaller or lower value in any regression model. The smaller the RSS, the better the model fits the data