Which reconstruction approach should the Specialist use to preserve the integrity of the dataset?

Explanations:

Listwise deletion removes entire rows with missing data, which could lead to loss of valuable information, especially when missing data is substantial (30% here).

Last observation carried forward fills missing values with the last observed data, which is not suitable for reconstructing data based on other columns or patterns.

Multiple imputation creates multiple sets of plausible values for missing data based on existing patterns, preserving dataset integrity and variability.

Mean substitution replaces missing data with the column’s mean, which can introduce bias and reduce variability, undermining the integrity of the dataset.