Analyze a labeled count table and keep the full evidence
Prepare the CSV axes and integer counts, choose alpha and correction, and save every matrix with its exact original source.
Prepare both axes and complete counts
The first header cell names the row axis; the remaining headers name columns. Later rows start with a row label followed by nonnegative integers. CSV quoting, duplicate labels and zero margins are retained. Percentages, missing counts and individual records are unsuitable. File mode does not process the paste box.
Genotype,Impaired,Control
E2E2,0,2
E2E3,7,30
E2E4,1,7
E3E3,34,133
E3E4,41,65
E4E4,8,5
- Distinguish duplicate labels by original index.
- Alpha can be 0.05 and must be strictly between 0 and 1.
- An original 3×3 table remains 3×3 when a zero margin is retained and is ineligible for Yates.
Check diagnostics and save all eight files
Check N, original shape and positive-margin shape before reading df, p, log p and cell states. Interpret small expected counts within the study design; an undefined test is not a successful null result. The page previews at most 16 cells and 4,000 codepoints; the report and five matrices retain every cell.
| File | Purpose to verify |
|---|---|
| observed.csv | Original nonnegative counts |
| expected.csv | Complete expected counts under independence |
| contributions.csv | Per-cell chi-square contributions; zero margins are blank |
| pearson-residuals.csv | Signed Pearson residuals |
| standardized-residuals.csv | Margin-adjusted residuals; undefined cells are blank |
| contingency-report.json | All cells, states, margins, indices, original spans and inference |
| settings.json | Actual source identity, hash and parameters |
| source-original.csv | Byte-exact original, including BOM and line endings |
Recover with the same original after failure
The complete 30-second deadline begins before native file capture and continues through validation, cleanup and first publication. Cancellation or timeout leaves no partial download; the same selection and parameters can run in a fresh worker. An input or setting change cancels the previous run and clears its success artifacts.
- Repair invalid counts, non-UTF-8 bytes or CSV quoting before retrying.
- If dimensions, active df or joint budgets are exceeded, adjust the scope before running.
- Keep the original and settings with a copied full report for review.
References
- Original aggregate-table inference discussion
The complete public 6×2 table totals 333. A reply recommends an asymptotic table test; no final author confirmation or private million-count table is supplied.
Tools in this category
Expand a tool to see its steps, options and supported formats, then open its workspace.
Contingency table inferenceCalculate a chi-square independence test directly from aggregate counts, with complete expected cells, contributions and residuals.
Use a two-axis frequency table to inspect margins, asymptotic evidence and the cells behind it. Select the active input, alpha and original 2×2 correction explicitly.
Steps
- Select the active input and provide the complete labeled count table.
- Enter alpha explicitly and choose correction using the original shape.
- Check the total, active degrees of freedom, small expected counts and undefined states.
- Save all eight complete files and interpret the asymptotic result in the study design.
Available options
- Active input
- Paste complete CSV · One original CSV file
- Significance level α
- 0.05
Must be strictly between 0 and 1.
- Yates correction for an original 2×2 table
- Off by default
Capabilities and limits
- Select paste or file as the active input. Use strict UTF-8 comma-separated CSV with nonempty labels on both axes: 1–64 data rows, 1–64 data columns, at most 4,096 cells and 4 MiB. Duplicate labels retain their original indices.
- Counts are nonnegative integers with total N ≤ 10¹². Alpha is an explicit finite number between 0 and 1. Yates applies only to the original 2×2 shape; removing zero margins does not make a larger original table eligible.
- All original rows, columns and zero-margin cells remain. Positive-margin degrees of freedom must be ≤ 100. Zero total or insufficient positive margins produce explicit undefined states. Positive expected counts below 5 warn about the asymptotic approximation.
- The upper tail uses direct positive terms and log arithmetic. Representable small p values retain their value; genuine binary64 underflow retains finite log p. This is an asymptotic independence test and does not reconstruct individuals or perform exact, Fisher or simulation tests.
- One operation shares 10 million work units, 512 MiB memory and a complete 30-second deadline including source read, worker startup, computation, complete validation, cleanup and first publication. Files plus full text allow 32 MiB, compact typed data including native metadata 8 MiB, their aggregate 40 MiB, and binary plus transport metadata 64 MiB. A crossed budget fails the whole operation.
- Download five complete matrices, the full report, settings and the exact original CSV. Screen previews are bounded; full copy and downloads are complete. The original, its filename and settings are processed locally in the current browser.