StratumStratum vs Jamovi & JASP
Jamovi and JASP are the popular free, open-source, R-backed statistics apps — the natural comparison when you're weighing paid against free on a Mac or Windows PC. Here's an honest, side-by-side look.
Jamovi and JASP are the two apps people mean when they ask, "is there a free alternative to paid stats software?" Both are free, both are open source, both are built on R, and both run on Mac, Windows, and Linux. That's a genuinely strong offer, and it deserves a straight answer rather than a sales pitch. Stratum is a paid app — so the only honest way to write this comparison is to say clearly where free is the right call, and where paying for Stratum actually buys you something you can't get for nothing.
Where Jamovi and JASP shine
Start with the obvious: they're free and open source, which removes the single biggest barrier to trying serious statistics — and for a student, a classroom, or a tight budget, that can settle the matter on its own. Both have friendly, approachable interfaces that lower the intimidation of a stats package. Both cover the classical toolkit — descriptives, t-tests, ANOVA, correlation, chi-square, regression — competently, with results computed through well-worn R packages. Both are widely used in teaching and backed by active communities. And JASP in particular is a leader in Bayesian methods, with a depth there that Stratum doesn't attempt to match, plus clean APA-formatted output that researchers value. None of this is faint praise — for a large share of everyday analysis, either app will do the job without costing a cent.
Two free apps, briefly
They're not interchangeable. JASP leans academic: its Bayesian analyses are a headline feature, its output is APA-styled and paper-ready, and its layout pairs each analysis with its results. Jamovi feels more like a spreadsheet you run analyses on, and its real trick is extensibility — a module library, and the R language underneath, lets you add methods the core doesn't ship. If your reason for going free is Bayesian depth, JASP; if it's a familiar data-grid workflow you can extend, Jamovi.
Where a paid native app earns its price
So what does paying for Stratum buy? Three things the free apps aren't built for. First, scale: Stratum's native engine handles up to about five million rows, where R-backed apps hold data in memory and slow down well before that. Second, a charts and data-visualization story — 30+ interactive charts, SPC control charts and process capability, and a polished report you can hand to someone. Third, a published validation record: Stratum's numbers are verified against R, the NIST StRD reference datasets, and SPSS, and that record is public. The open-source apps are inspectable by nature — a different, also-legitimate kind of trust — but Stratum ships the verification done for you. It's also native to Mac and Windows rather than one cross-platform toolkit rendered on both. Whether those are worth the price is exactly your call to make.
| Stratum | Jamovi | JASP | |
|---|---|---|---|
| Price | Paid, one-time ($119 / $249) | Free | Free |
| Licence | Commercial | Open source | Open source |
| Platforms | Native Mac & Windows (built to each) | Cross-platform (Mac / Windows / Linux) | Cross-platform (Mac / Windows / Linux) |
| Backed by | Native Swift/C# engine | R | R |
| Classical stats | Descriptives, t-tests, ANOVA + Tukey, MANOVA, correlation, chi-square, regression (VIF / Cook's D) | Solid, well-covered | Solid, well-covered |
| Bayesian methods | Not a Bayesian tool (frequentist + ML) | Available via module | Extensive — a signature strength |
| Charts | 30+ interactive (box, violin, density, Q-Q, Pareto, mosaic, control charts) | Analysis-linked plots (fewer chart types) | Analysis-linked plots, clean output |
| SPC / control charts + capability | Yes | Not a focus | Not a focus |
| Machine learning | PCA, clustering, decision trees, random forests, boosted trees | Via modules | Some (classification / regression modules) |
| Max data size | Up to ~5 million rows | In-memory (R); slows on large data | In-memory (R); slows on large data |
SPSS .sav import | Yes (1.4) | Yes | Yes |
| Validation record | Published — verified vs R, NIST StRD, SPSS | Open source; results run through R packages | Open source; results run through R packages |
| Report / export | Report PDF + charts PNG/PDF (RTF / APA-style coming) | Results export (PDF / HTML) | Results export incl. APA-formatted tables |
| Best for | Fast native everyday analysis at scale, charts, a trustworthy report | Free teaching & everyday classical stats, extensible via R | Free Bayesian + frequentist analysis, tidy APA output |
Two rows are parity, not victory, and worth calling out so the table isn't misread. Both Jamovi and JASP open .sav files too, so SPSS import isn't a Stratum-only win here. And all three run on Mac and Windows — the difference is that Stratum is built natively to each platform rather than released through a single cross-platform codebase, not that it reaches more platforms.
The core overlap
Set expectations honestly: for the bread-and-butter of applied statistics — descriptives, t-tests, one-way and factorial ANOVA, correlation, chi-square, and regression — all three tools will get you a correct answer. If that's the whole job, the free apps are not a compromise; they're a complete solution. The overlap is real and large, and pretending otherwise would waste your time. Stratum's case begins where that shared core ends: at data volume, at the breadth and interactivity of the charts, at machine learning sitting beside the classical tests, and at a report and a validation record you can put in front of someone else.
Trying it on your own data
You don't have to decide from a table. Stratum opens your .csv, .xlsx, and .sav files directly, so you can run your own analysis side-by-side with whatever free app you're already using and judge on your own data. If you're coming from SPSS files specifically, opening a .sav on Mac works the same way in all three.
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Frequently asked questions
Is Stratum free like Jamovi and JASP?
No — Stratum is a paid app (one-time, $119 / $249), where Jamovi and JASP are free and open source. Stratum's case is scale, charts, a validation record, and a native Mac-and-Windows experience; if those don't matter to you, the free apps are excellent.
What does JASP do that Stratum doesn't?
Bayesian statistics. JASP's Bayesian methods are a signature strength and are far deeper than Stratum's, which is a frequentist-plus-machine-learning tool.
Are Jamovi and JASP good enough for real work?
Yes. Both compute through mature R packages and cover the classical toolkit well. The question isn't whether they're capable — it's whether you need Stratum's scale, charting, reporting, and validation on top.
Do Jamovi and JASP run on Mac?
Yes, both are cross-platform (Mac, Windows, Linux). Stratum is built natively for Mac and Windows rather than shipped through one cross-platform toolkit.
Can I open an SPSS .sav file in all three?
Yes — Stratum (from 1.4), Jamovi, and JASP all read .sav files directly.
Which should I choose?
Free and Bayesian → JASP. Free and extensible with a data-grid feel → Jamovi. Large data, a deep charts-and-report story, and a validated native app you're willing to pay once for → Stratum.
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