Validation and release limits

Executed checks

The companion was executed in a Linux workspace using Python 3.12.14, NumPy 2.3.5, SciPy 1.17.0 and Matplotlib 3.10.8. Editorial HTML uses Markdown 3.11.1. Exact versions describe this environment; they do not guarantee installation on every operating system or future package index.

The suite has 76 passing tests (66 data/method checks and 10 public-checker checks) covering fixture construction, raw cleaning, count reconciliation, conflicting duplicates, summaries, linear quartiles, missingness, independent calculations against SciPy, mean intervals, Welch contrast/CI/test, regression and sampling demonstrations. Data and numerical outputs were regenerated from another working directory and compared byte-for-byte; checksums and scope are recorded in outputs/data_reproducibility.json.

An independent reviewer recomputed the published values directly from CSV using decimal arithmetic/manual interpolation and SciPy without importing the reference analysis or generator. The check covered 690 numerical comparisons, including raw reconciliation, summary values, missingness, effect direction, interval/test compatibility and regression. Teaching-sequence and audit issues found in review were corrected. The complete narrative, workbook, explained solutions, assessments and capstone were also reviewed independently. Review identified a conflicting-duplicate audit edge case, an exercise using inference before it was taught, a filename error and an overly broad probability-zero statement; all were corrected. Visual review also prompted moving an overlapping legend and making chart scope visible.

Static package checks cover 279 checks across three HTML pages, 96 local references, nine SVGs and all exercise/answer identifiers. The optional unfinished learner starter was executed and failed as intended; an independently calculated completed payload passed the 12 public arithmetic/label checks, while a reversed effect failed. The checker does not assess the quality of a limitations statement or recommendation.

Nine original SVG visuals have explicit titles/descriptions and text alternatives in the reading pages. Their matching PNG renders were visually inspected for readable labels, clipping and scale/legend consistency. This is chart-artifact inspection, not a browser or screen-reader test.

What is not verified

No end-to-end reading or navigation session has been run in a desktop or mobile browser. Print output, zoom/reflow, keyboard navigation, native CSV handling, macOS/Windows installation, spreadsheet formulas, Aabha browser-lab compatibility and assistive-technology behavior are not certified. Static semantics and contrast-conscious styling are useful preparation, but they do not establish WCAG conformance. No beginner learner pilot, assessment calibration or measured completion-time study has been conducted.

No site was published, no Mac or VPS was used, no learner account was created and no real dataset was processed. This is an offline course-content package for review.

Acceptance checklist before public teaching

• Extract the ZIP on each target operating system; open index.html and check every image and local link.
• Follow the navigation with only a keyboard; verify visible focus, skip link and reachable scrollable tables.
• Inspect phone-width layouts and 200%/400% zoom. Text must remain readable without clipping; tables may scroll horizontally with an obvious affordance.
• Test a screen reader through headings, table headers, chart alternatives and page navigation. Check that descriptions provide the same core conclusions as the images.
• Print representative lesson, table-heavy and chart pages; inspect page breaks and clipping.
• Recreate a fresh optional Python environment and execute setup, generator, analysis, charts and tests on each advertised OS.
• Complete the learner starter rather than only running reference tests; confirm expected incomplete-starter failure and corrected-result success.
• Ask beginners to attempt exercises before seeing solutions, record actual time and misconception patterns, and revise pacing and prerequisites.
• Have two instructors score sample capstones and reconcile rubric disagreements before representing a threshold as reliable.
• Recheck external references and dataset/assessment consistency after any editorial change.