Quanta's engine is pure Swift on Apple's Accelerate framework, with zero R or Python at runtime. R and Python are used only as validation oracles during development: we compute reference values with them, match our output to many digits, then ship none of their code.
One dataset, eight statistics, run through ReliCheck (Swift), R 4.6 (base), and Python 3 (scipy / statsmodels). All three reading one identical CSV, printed to ten decimal places.
| Statistic | ReliCheck (Swift) | R 4.6 | Python 3 |
|---|---|---|---|
| Mean | 7.0500000000 | 7.0500000000 | 7.0500000000 |
| SD (n−1) | 1.4680814548 | 1.4680814548 | 1.4680814548 |
| Pearson r | 0.9231537124 | 0.9231537124 | 0.9231537124 |
| Welch t | 2.7410956645 | 2.7410956645 | 2.7410956645 |
| One-way ANOVA F | 21.9666666667 | 21.9666666667 | 21.9666666667 |
| OLS slope | 0.1015741992 | 0.1015741992 | 0.1015741992 |
| OLS R² | 0.3449057973 | 0.3449057973 | 0.3449057973 |
| Cronbach alpha | 0.9334426230 | 0.9334426230 | 0.9334426230 |
All three agree to ten decimal places on every statistic.
Every engine is validated against an independent reference, not just internal consistency.
| Method | Reference oracle | Agreement |
|---|---|---|
| Univariate summary | NIST StRD (certified) | mean 12+ digits; SD ~8 (cancellation-safe) |
| Linear regression | NIST StRD Norris | coefficients, SEs, R² to 9-10 digits |
| t-tests / ANOVA / ANCOVA | R t.test, aov, car | exact / matched |
| Correlation & nonparametrics | R cor; hand-computed | exact / closed-form |
| Logistic / Poisson / ordinal | R glm, MASS::polr | coefficients to 1e-3 |
| Reliability (alpha, omega) | R / Python; closed-form | 10 digits / 1e-5 |
| Factor analysis & PCA | independent Python; closed-form | recovers simple structure |
| Repeated-measures ANOVA | R afex / ez + SPSS GLM | F, partial η², Mauchly, GG/HF matched |
| MANOVA / discriminant / canonical | R manova, MASS::lda, cancor | test statistics matched |
| Multiple imputation (MICE) | R mice + Rubin's rules | pooled estimates, variance, FMI matched |
| SEM / CFA | R lavaan (Holzinger-Swineford) | χ² exact; CFI/TLI/RMSEA/SRMR to 3 figs |
| Complex-survey SE | R survey (svymean) | mean/SE to 1e-6 / 1e-4 |
The SPSS and Stata readers are pure Swift. They are tested by round-tripping genuine binary files (SPSS .sav, Stata .dta releases 117-119) written by a ReadStat-based writer: variable names, rows, variable labels, and value labels read exactly. Value labels are exposed but never substituted into cells, so statistics are computed on the values you recorded.
Reviewers accept results from software they can verify. This record is the evidence. Quanta ships as one version-stamped, notarized binary with a method file, so the version flows straight into your Methods section: R-level accuracy with no R or Python to install, plus honest-stats guardrails the big packages do not give by default.