I've got a good feeling about Option B. Residual plots and standardized residuals are classic ways to spot outliers and influential points. I'll walk through the logic of that approach and see if it makes the most sense.
Option C seems like it might be the way to go. I remember learning about leverage and Cook's distance as ways to detect influential observations. I'll double-check the details, but that's my initial thought.
Hmm, I'm not entirely sure which approach would be best here. I'll need to review my notes on regression diagnostics to see which method is most appropriate for identifying influential points.
This looks like a tricky question. I'll need to think carefully about the different options and how they might identify influential observations in a multiple regression model.
Daryl
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