Example Concept: Imputation is a common strategy where missing values are replaced with substituted values. Techniques include mean, median, or mode imputation for numerical data, and using the most frequent value for categorical data. More advanced methods involve using predictive models to estimate missing values or employing algorithms like k-nearest neighbors (KNN) that can handle missing data inherently. It's important to assess the impact of imputation on the dataset's variance and bias.