SPSS vs Jamovi vs JASP: Which Should Filipino Graduate Students Use in 2026?

Every term, a new batch of graduate students asks us the same question at StatAce: “Which software should I actually use for my thesis?” It’s a fair question. SPSS has been the default in Philippine academia for decades, but it’s a paid subscription product, and not every student or department can afford it comfortably. Jamovi and JASP have emerged as free, capable alternatives, and both are genuinely good options, not just budget substitutes. Here’s how the three actually compare, and how to decide which fits your situation.

The Short Version

• SPSS remains the safest default if your program, panel, or adviser expects it, and if cost isn’t a major constraint. It’s still the most widely recognized package in Philippine academic circles.
• Jamovi is the best free alternative for most thesis-level quantitative work. It has an editable spreadsheet interface, formula-based computed variables, and a growing module library that covers most tests graduate students need.
• JASP is the best choice if your study benefits from Bayesian analysis alongside classical tests, or if you prefer its interface. Both jamovi and JASP grew out of the same frustration with SPSS pricing, and jamovi was actually started by former JASP developers, so the family resemblance between the two is strong.

Cost: The Biggest Practical Difference

This is usually the deciding factor for students, so let’s be direct.

SPSS is licensed as a recurring subscription rather than a one-time purchase. Base pricing has historically started around $99 per user per month, or about $1,290 per year for the base package, with add-on modules (advanced statistics, custom tables, regression, and others) priced separately. Many Philippine universities and colleges provide SPSS access through an institutional license, so check with your school’s IT office or library before paying for it yourself. Pricing and available student or institutional discounts change often, so always confirm the current rate directly with IBM or your school rather than relying on a number from a blog post, including this one.

Jamovi and JASP are both free and open source, with no license fee, no expiration date, and no watermarking on your output. This alone makes them attractive for students who are self-funding their thesis costs or whose institution doesn’t provide an SPSS license.

Ease of Use and Interface

All three tools use a similar point-and-click, spreadsheet-style interface, a deliberate design choice in jamovi and JASP to feel familiar to SPSS users making the switch.

SPSS has the most mature and heavily documented interface, with decades of textbooks, YouTube tutorials, and university guides built around it. If you’re following a specific published methodology or a professor’s exact instructions, those instructions were likely written with SPSS screenshots.

Jamovi offers a genuinely editable data spreadsheet (you can create computed variables with live formulas that update automatically, similar to Excel) and results that update in real time as you change your analysis options. It also shows the underlying R syntax behind each analysis if you want to see it, which is a nice bridge for students who may eventually want to learn R.

JASP has a slightly more restricted, read-only data view, but its output tends to be polished and close to APA formatting out of the box, which can save you time when you’re building your results chapter.

Statistical Capabilities

For the vast majority of graduate theses in business, education, and social science, all three tools cover the same core ground: t-tests, ANOVA, correlation, regression, chi-square, and reliability analysis (Cronbach’s alpha), and for these core tests, the underlying numbers from jamovi and JASP will match each other, since both run on R under the hood.

Where they start to differ:

Bayesian statistics. This is JASP’s signature strength. Nearly every classical test in JASP- t-tests, ANOVA, regression, correlation- has a Bayesian counterpart available in the same menu, at the same level of effort as running the classical version. If your research question specifically calls for quantifying evidence in favor of a null hypothesis, or your adviser wants a Bayesian analysis included, JASP is by far the more convenient choice. Jamovi can do Bayesian analysis too, but through additional modules rather than as a built-in, first-class option throughout the whole program.

Extensibility and module libraries. Jamovi has a larger and more active library of add-on modules (contributed by its user community) covering things like SEM, reliability analysis extensions, meta-analysis, and more specialized procedures. If your study needs a fairly specific or niche statistical technique, jamovi is somewhat more likely to have a module for it.

Structural Equation Modeling (SEM). If your thesis requires SEM with latent variables, none of these three tools is really the natural home for that work. AMOS (bundled with or purchased alongside SPSS), lavaan in R, or dedicated SEM software like Mplus remain the standard choices. Jamovi has SEM-related modules, but for a full measurement model with confirmatory factor analysis and structural paths, most Philippine graduate programs and panels will still expect AMOS output, so check with your adviser before assuming Jamovi’s SEM module is an acceptable substitute.

What Your Panel Actually Cares About

Here’s something worth saying plainly: in our experience, panels generally care more about whether your analysis is correct and well justified than about which software produced it. That said, a few practical realities matter:

• If your program has a long-standing tradition of SPSS output in past theses, using something else may raise questions your adviser has to field for you, even if the numbers are identical. Ask early rather than assume.
• If you’re required to submit raw output files (.spv for SPSS) as part of your appendix, switching software mid-thesis can create extra work reformatting your results.
• Reviewers unfamiliar with jamovi or JASP output format may ask what it is. A short explanatory note or appendix (“Analysis conducted in jamovi, an open-source statistical package built on R”) is usually enough to satisfy that question.

Our Recommendation

If cost isn’t an obstacle and your program expects SPSS: stick with SPSS. There’s little practical benefit to fighting institutional convention over a free alternative when a paid license is already available to you.

If cost is a real constraint and your study uses standard tests (t-tests, ANOVA, regression, correlation, reliability analysis): jamovi is our default recommendation. It covers most thesis-level analysis needs, has an active support community, and its interface will feel familiar if you’ve used SPSS before.

If your study specifically calls for Bayesian methods, or you prefer JASP’s cleaner, more APA-ready output: JASP is an equally strong free choice, particularly for straightforward comparative and correlational designs.

If your study involves SEM with latent variables: none of these three should be your primary tool. Plan on AMOS or a dedicated SEM package regardless of which software you use for your preliminary descriptive and reliability analysis.

The Bottom Line

There’s no universally “correct” choice between SPSS, jamovi, and JASP. All three can produce statistically identical results for standard analyses, since jamovi and JASP both run on the same open-source R engine underneath their interfaces. The decision usually comes down to your budget, your program’s expectations, and whether your specific analysis (Bayesian methods, SEM, a niche test) pushes you toward one tool’s particular strengths.

If you’re not sure which tool fits your research design, or you’d like help running your analysis in whichever software you choose, that’s exactly what StatAce helps with.

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Not sure which statistical software fits your thesis, or need help interpreting your output once you have it? Reach out to StatAce; we help Philippine graduate students and researchers choose the right tools and run defensible analyses.