Tag Archives: MAR

Outliers and missing values are the most important for any data science engineers need to deal with, we already discussed about outliers. Before talking about how to deal with missing values, let’s talk about types of missing values. Missing at Random (MAR) Missing completely at random (MCAR) Missing not at Random (MNAR) Let’s take one example,Continue reading “Missing Data Analysis with MICE”