What is mean imputation?
An example of an AI chatbot conversation about mean imputation in data analysis.
Can you explain what mean imputation is?
Mean imputation is a technique used to fill in missing values in a dataset by replacing them with the mean of the available values.
When should I use mean imputation?
You should use mean imputation when the missing data is random and the dataset is large enough to ensure that the mean is a good estimate.
Are there any drawbacks to using mean imputation?
Yes, mean imputation can reduce variability in the dataset and may lead to biased estimates if the data is not missing at random.
What are some alternatives to mean imputation?
Alternatives include median imputation, mode imputation, or using more advanced techniques like regression or multiple imputation.
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