Outliers
a. |
are scores that are similar to the rest of the data |
|
b. |
bias parameter estimates but not their associated estimate of error |
|
c. |
bias parameter estimates and their associated estimate of error |
|
d. |
do not bias parameter estimates and their associated estimate of error |
I believe it is C... am I correct?
Estimation can be affected by the presence of outliers, observations which deviate far from the linear relation of the response variable and the exploratory variables.Ordinary least squares estimator is extremely sensitive to multiple outliers in linear regression analysis. It can even be easily biased by just a single outlier.
Presence of man-made or random outlier, or both, would seriously influence the results of statistical analyses including point and interval estimates, and type I and type II errors.
Hence option C is correct
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