Imputing missing values with the mean is always better than using the median, as it provides a more accurate representation of the central tendency.

Imputing missing values with the median is always better than using the mean, as it is more robust to outliers and skewed distributions.

Imputing missing values with the mean is more appropriate when the distribution of 'Income' is symmetric and has no extreme outliers, while using the median is more suitable when the distribution is skewed or has extreme outliers.

The choice between imputing with the mean or median does not matter, as both approaches will lead to the same results in the model.