# Data Imputation

Skill · Data Science, Analytics and AI/ML

Canonical page: https://career.thegoodapps.co/skills/data-imputation

Data imputation is the statistical technique of filling in missing or incomplete data values with substituted estimates, such as the mean, median, mode, or model-predicted values. Data scientists and statisticians use imputation to preserve dataset size and avoid the bias or errors that missing values can introduce into analysis or machine learning models. Common methods include mean/median substitution, k-nearest neighbors, regression imputation, and multiple imputation.

Related skills: [Statistical Analysis](https://career.thegoodapps.co/skills/statistical-analysis), [R](https://career.thegoodapps.co/skills/r), [Machine Learning](https://career.thegoodapps.co/skills/machine-learning), [Data Cleansing](https://career.thegoodapps.co/skills/data-cleansing)

## Open roles requiring Data Imputation (0)

None of the roles we have read name this skill yet. A large share of the visible corpus has not been parsed for skills, so this is at least as likely to be our backlog as the market's verdict.