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Answer: When the data is categorical and the mode represents the most frequent category.
Replacing missing values with the mode is appropriate when the data is categorical, as the mode represents the most frequent category. This method is simple and effective for categorical variables where the mode is a meaningful representation. However, it is not suitable for numerical data, as the mode does not provide a measure of central tendency for numerical variables. Additionally, if the data is not missing at random, using the mode might introduce bias.
Author: LeetQuiz Editorial Team
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Under what circumstances is replacing missing values with the mode value considered an appropriate method for handling missing data? Discuss the limitations of this approach and when it might not be suitable.
A
When the data is normally distributed and the missingness is random.
B
When the data is categorical and the mode represents the most frequent category.
C
When the data is numerical and the mode is a good representation of the central tendency.
D
When the data is skewed and the mode is a good representation of the central tendency.
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