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Discuss the implications of using mean imputation for a numerical feature in a dataset where the missing values are not missing at random. Explain how this could bias the model and suggest an alternative approach to handle such missing data.
A
Mean imputation can introduce bias if the missingness is related to the target variable.
B
Mean imputation is always unbiased and appropriate for all types of missing data.
C
Mean imputation should not be used for numerical features.
D
Mean imputation is only suitable for categorical features.
