The LabPRO
Pitfall Detector
Check data work, whether done by people or by AI, for common pitfalls before you share it. Upload a chart, paste a written analysis, drop in a slide deck or analysis code, or bring every piece of an analysis at once, and get specific findings you can act on.
Built on datapitfalls, the open-source detector based on Ben Jones’s Avoiding Data Pitfalls. Every finding cites a rule from its taxonomy of pitfalls across eight domains, with why it matters and how to avoid it.
Mistaking the data for reality: overgeneralizing from limited evidence, or treating numbers as more certain than they are.Mishandling the data itself: dropped rows, broken joins, mismatched keys, or inconsistent categories.Calculation slip-ups: mixing units, averaging rates without weighting, or aggregating across uneven periods.Comparison and inference errors: treating an average as typical, ignoring uncertainty, or over-reading small samples.Flawed analysis: extrapolating a trend too far, overfitting a model, or choosing a metric that flatters the story.Charts that mislead: truncated axes, the wrong chart type, cherry-picked windows, or missing context.Design choices that trip up the reader: colorblind-unsafe palettes, inconsistent colors, or unclear interactions.Who or what the data leaves out: unheard voices and missing groups that skew the whole picture.
Hover or tap a domain to see what it covers.
Pro subscription required
The Pitfall Detector is available to Pro subscribers.
Pro includes
- • Every course in the library
- • AI Coach for personalized guidance
- • AI Tutor on every lesson
- • Pitfall Detector in the Lab
- • Badges and shareable verification
$29 / month or $290 / year. 7-day money-back guarantee.
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