I need to interpret a residual table which was fitted by an analyst plotting $y_.0123$ (final residual) against the $x_{1.023}$. The table represents residuals produced by each variable.
data
pts Y_.0123 Bo B1 B2 B3
212 small small small small small
14 small small large small small
10 small small small large small
2 small small small small large
2 small large small small small
2 large large large large small
I need to interpret the table and make suggestions. It is an appropriate assumption to state that the small residuals should remain in the model since they are relative to the $y$. The last 3 rows with data point of 2 should be removed since they are causing residuals to be possible outliers or can be data errors. Also removing B1 and B2 will improve since they will eliminate the large residuals remaining. What beta will be affected if I remove B1 and B2?
