Testing assumptions for factor analysis is crucial to ensure the validity and reliability of the results.
By testing these assumptions, researchers can ensure the robustness and validity of their factor analysis results. If assumptions are violated, appropriate corrective measures such as data transformation, removing outliers, or using alternative factor analysis methods may be necessary.