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Another important approach for dealing with missing data is multiple imputation. Instead than substituting a single value for each missing data point, multiple imputation replaces the missing values with a variety of probable values that account for the natural variability and uncertainty of the right values.

Imputation is the process of replacing missing data with replaced values in statistics. It's called "unit imputation" when substituting for a data point, and "item imputation" when substituting for a component of a data point.

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