With regard to regression, which of the following statements about outliers are true?
I. Outliers have large residuals.
II. A point may not be an outlier even though its x-value is an outlier in the x-variable and its y-value is an outlier in the y-variable.
III. Removal of an outlier always sharply affects the regression line.

Question

With regard to regression, which of the following statements about outliers are true?
I. Outliers have large residuals.
II. A point may not be an outlier even though its x-value is an outlier in the x-variable and its y-value is an outlier in the y-variable.
III. Removal of an outlier always sharply affects the regression line.

anonymous · Answer

@texaschic101 @Compassionate

alexandervonhumboldt2 · Answer

i tihnk B but no sure

anonymous · Answer

what do you think @SithsAndGiggles

anonymous · Answer

it can be more then one too if that helps  @AlexandervonHumboldt2

anonymous · Answer

@nincompoop @TheSmartOne

anonymous · Answer

@pooja195

anonymous · Answer

Certainly, option I is true. Outliers are by definition far away from the average/median/mode/whatever measure of central tendency you use.

alexandervonhumboldt2 · Answer

i dpnt knwosorry
think only this but no sure

anonymous · Answer

do you think both one a two could be true? @SithsAndGiggles

anonymous · Answer

I'm not sure I follow what's being said in option II. What does it mean for the x-variable to contain an outlier?

anonymous · Answer

i guess it means if your range for the x is  1-10 and the x variable given is something like 50

anonymous · Answer

never mind i think i got it, thank you!!