Which is an approach for dealing with missing data?
A) for metric variables, estimate the missing values by substituting the mean
B) for nonmetric variables, estimate the missing values by substituting the mean
C) for metric variables, estimate the missing values by substituting the standard deviation
D) for nonmetric variables, estimate the missing values by substituting the standard deviation
E) for metric or nonmetric variables, estimate the missing values by substituting the kurtosis

Question

Quizplus · Accepted Answer

For metric variables, it is appropriate to estimate the missing values by substituting the mean. This is because the mean represents the central tendency of the data and does not change the overall distribution of the data. Substituting the standard deviation or kurtosis would not be appropriate as these measures are based on the variability and shape of the data, respectively, and would change the distribution of the data. For nonmetric variables, other approaches such as using mode or imputation techniques may be more appropriate.

Which Is an Approach for Dealing with Missing Data