Check measurement types and missing-value codes before choosing an analysis. Use a small known dataset to learn the output layout, then save the project with its analysis options. Read the method's assumptions and report effect sizes or uncertainty where appropriate rather than relying solely on significance values.
This is best suited to students and researchers doing common statistical analyses. Before committing a larger project, account for these trade-offs: advanced methods may need modules; large datasets depend on available memory.
