Each of 124 statistical methods is compared with reference results, most of them published worked examples. Every method passed at the tolerances recorded for it.
The check compared 497 cases, with 8,394 numerical comparisons and 716 exact comparisons. It ran on 2026-11-06, and the source files of the statistical engine have not changed since.
These figures describe the listed cases and not every possible input. Agreement is against stored reference numbers, so a rounded published figure or a simulation can agree to fewer digits and still pass. No statistician has yet reviewed the methods for DBARDO LTD, and this page is not a certification.
| Method | Cases | Comparisons |
|---|---|---|
| Analyse a response surface design | 4 | 117 |
| Analyse a two-level factorial design | 3 | 58 |
| Anderson–Darling normality | 2 | 4 |
| Attribute agreement study | 1 | 22 |
| Attribute gage aiag | 6 | 140 |
| Average and range chart | 4 | 25 |
| Average and standard deviation chart | 4 | 26 |
| Bartlett variance test | 1 | 2 |
| Best subsets regression | 2 | 22 |
| Binary logistic categorical | 2 | 24 |
| Binary logistic regression | 6 | 245 |
| Binary probit regression | 2 | 41 |
| Binomial capability | 5 | 198 |
| Bonett two variance test | 4 | 24 |
| Bonett variance test | 3 | 21 |
| Box-Cox process capability | 3 | 16 |
| Capability sixpack | 5 | 40 |
| Chi-square association | 2 | 5 |
| Chi-square goodness of fit | 3 | 6 |
| Control chart boxcox | 7 | 106 |
| Control chart g | 2 | 14 |
| Control chart imr rs | 3 | 68 |
| Control chart median | 10 | 213 |
| Control chart moving average | 3 | 48 |
| Control chart t | 3 | 21 |
| Control chart zmr | 2 | 55 |
| Create a response surface design | 6 | 74 |
| Create a two-level factorial design | 3 | 20 |
| Cross tabulation | 1 | 7 |
| Crossed measurement system study | 2 | 23 |
| Defect count chart | 5 | 29 |
| Defects and yield | 3 | 8 |
| Defects per unit chart | 4 | 23 |
| Descriptive statistics | 2 | 6 |
| Discriminant analysis | 3 | 51 |
| Distribution identification | 9 | 69 |
| Dixon test | 4 | 12 |
| Equivalence one sample ttest | 3 | 39 |
| Equivalence paired ttest | 2 | 26 |
| Equivalence two sample ttest | 4 | 52 |
| Exponentially weighted moving-average chart | 1 | 23 |
| Factor analysis | 5 | 167 |
| Fisher exact test | 39 | 131 |
| Friedman test | 2 | 12 |
| Gage linearity bias | 2 | 80 |
| Gage rr expanded | 3 | 89 |
| Gauge comparison | 2 | 26 |
| General factorial analysis | 1 | 85 |
| General factorial design | 1 | 3 |
| General linear model | 8 | 618 |
| General linear model mixed | 6 | 106 |
| Grubbs test | 3 | 12 |
| Individuals and moving-range chart | 7 | 34 |
| Johnson process capability | 8 | 59 |
| Kruskal–Wallis test | 2 | 4 |
| Laney P-prime chart | 1 | 5 |
| Laney U-prime chart | 1 | 6 |
| Latin square analysis | 1 | 112 |
| Latin square design | 1 | 2 |
| Levene and Brown–Forsythe variance test | 1 | 2 |
| Lilliefors | 3 | 12 |
| Lognormal process capability | 6 | 38 |
| Mann–Whitney test | 9 | 49 |
| Manova | 2 | 44 |
| Mixture analysis | 3 | 307 |
| Mixture design | 2 | 8 |
| Model reduction | 2 | 26 |
| Mood median test | 2 | 4 |
| Multiple linear regression | 8 | 262 |
| Nested measurement system study | 2 | 19 |
| Nominal logistic regression | 2 | 48 |
| Normal process capability | 2 | 17 |
| Number nonconforming chart | 4 | 19 |
| One-proportion test | 2 | 6 |
| One-sample Poisson rate test | 3 | 10 |
| One-sample sign test | 2 | 5 |
| One-sample t test | 3 | 14 |
| One-sample Wilcoxon test | 3 | 6 |
| One-sample Z test | 4 | 60 |
| One-variance chi-square test | 5 | 85 |
| One-way analysis of variance | 12 | 245 |
| Ordinal attribute agreement | 6 | 168 |
| Ordinal logistic regression | 2 | 36 |
| Ordinal probit regression | 2 | 36 |
| Paired t test | 3 | 14 |
| Pearson correlation | 3 | 16 |
| Plackett burman design | 7 | 2,191 |
| Poisson capability | 4 | 280 |
| Poisson regression | 2 | 32 |
| Power equivalence one sample | 5 | 36 |
| Power equivalence paired | 5 | 36 |
| Power equivalence two sample | 9 | 65 |
| Power for one mean | 1 | 2 |
| Power for one proportion | 4 | 4 |
| Power for two means | 1 | 2 |
| Power for two proportions | 2 | 2 |
| Power one variance | 6 | 32 |
| Power one way anova | 3 | 19 |
| Power two level factorial | 4 | 25 |
| Power two variances | 6 | 32 |
| Principal components | 2 | 26 |
| Process capability between within | 2 | 18 |
| Proportion nonconforming chart | 4 | 23 |
| Randomised block analysis | 1 | 75 |
| Randomised block design | 1 | 2 |
| Regression categorical | 2 | 22 |
| Response optimiser | 10 | 50 |
| Runs tests | 2 | 4 |
| Sample size for a chosen margin | 29 | 203 |
| Shapiro wilk | 2 | 4 |
| Simple linear regression | 6 | 66 |
| Spearman correlation | 2 | 4 |
| Statistical tolerancing | 2 | 14 |
| Stepwise regression | 3 | 30 |
| Tabular cumulative-sum chart | 1 | 43 |
| Taguchi analysis | 3 | 60 |
| Taguchi design | 5 | 25 |
| Tolerance interval | 7 | 28 |
| Two-proportions test | 4 | 5 |
| Two-sample t test | 6 | 28 |
| Two-variance F test | 1 | 5 |
| Two-way analysis of variance | 3 | 451 |
| Type 1 gage study | 1 | 7 |
| Weibull process capability | 4 | 29 |
Each reference result comes from a published worked example or from a calculation made separately from Incra's own code. These are the pages that the cases cite.