One of the most common questions scholars ask is which statistics software to use. The honest answer: it depends on what your questions and data demand — not on which tool you already know.
SPSS — general statistics
SPSS is the workhorse for descriptive statistics, reliability (Cronbach's alpha), and classic tests: t-tests, ANOVA, correlation and multiple regression. If your study tests straightforward relationships between a few variables, SPSS is usually enough.
AMOS — covariance-based SEM
AMOS runs covariance-based Structural Equation Modelling (CB-SEM). Choose it when you are confirming an established theory, have a reasonably large and roughly normal sample, and care about model fit indices like CFI and RMSEA.
SmartPLS — variance-based SEM
SmartPLS runs Partial Least Squares SEM (PLS-SEM). It shines for prediction and complex models, tolerates non-normal data and smaller samples, and handles formative constructs — which is why it's popular in management and marketing research.
Confirming established theory with a large, normal sample? Reach for AMOS. Predicting or exploring a complex model, or working with a smaller/non-normal sample? Reach for SmartPLS. Just testing a few relationships? SPSS.
Can you use more than one?
Often yes. Many scholars clean data and check reliability in SPSS, then test their conceptual model in SmartPLS or AMOS. For a deeper comparison, see SPSS vs SmartPLS and AMOS vs SmartPLS.
Whichever you choose, interpretation is the point examiners test. Our data analysis mentoring coaches you to run and defend your own results — talk to a mentor.
Frequently asked
Is SmartPLS better than AMOS?+
Neither is universally better. AMOS (CB-SEM) is for confirming theory with larger, normal samples; SmartPLS (PLS-SEM) is for prediction, complex models and smaller or non-normal samples. Your research aim decides.
Can I do SEM in SPSS?+
Not in base SPSS. For covariance-based SEM you use the AMOS add-on; for variance-based SEM you use SmartPLS.
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