You are analyzing a dataset where some missing values have been replaced using mean imputation. What effect might this have on the variance of the data?
- It could cause overfitting
- It could create multicollinearity
- It could decrease the variance
- It could increase the variance
When missing values are replaced using mean imputation, it could decrease the variance of the data. This is because imputed values are just the mean of observed values and do not add any variability. Therefore, the overall variability of the data could be underestimated, leading to biased estimates.
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