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Missing Data Imputation

Statistical Glossary

Missing Data Imputation:

“Imputing missing data” is a process by which the missing values in a data set are estimated from the remaining data, for the purpose of allowing statistical procedures to be performed on a complete data set. (Most statistical procedures fail if some values in a data set are missing; so the purpose of estimating the missing values is simply to get around this problem.)

See the statistics.com course “Missing Data Analysis”

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