imputaatiomalli
Imputaatiomalli refers to a statistical method used to handle missing data in a dataset. When values are missing for certain variables, imputation models estimate and fill in these missing values based on the observed data. The goal is to create a complete dataset that can be used for further analysis without introducing significant bias or distorting relationships between variables.
There are various types of imputation models. Simple methods include mean imputation, where missing values are
The choice of imputation model depends on the nature of the missing data (e.g., missing completely at