Statistics and chart claims Chrome workflow

Fact-check statistics and chart claims on Chrome before citing or resharing them.

Start with one surprising statistic, chart, graph, poll result, percentage, trendline, infographic, benchmark, model score, dashboard screenshot, map label, or dataset-derived claim, then run a FactSentinel first-step source check before you trust the takeaway.

Open Download Page Review Economics Workflow

Start with the exact data claim.

Statistics and chart claims often compress the original dataset/report, sample size, denominator, date range, geography, methodology, sponsor, chart axis, missing baseline, uncertainty interval, corrections, and secondary-article framing into one visual or sentence. A practical Chrome workflow starts by isolating the exact numerical claim and checking whether the visible takeaway is supported by the underlying source trail.

Statistics/chart guardrail: FactSentinel helps audit the claim/source trail and model agreement around numerical claims. It is not a statistics package, data-forensics tool, financial adviser, medical adviser, legal adviser, guarantee of truth, real-time market feed, or verification of every live dataset.

1. Preserve chart context

Keep the title, axis labels, legend, source line, date range, geography, sample size, denominator, sponsor note, uncertainty interval, crop boundaries, caption, and exact claim before the chart gets paraphrased.

2. Run FactSentinel

Review data source trails, chart axes, time ranges, geography, denominators/base rates, methodology notes, sponsor context, uncertainty intervals, corrections, secondary-source overstatement, crop/context clues, caveats, confidence, reasoning, and model agreement.

3. Cite cautiously

Open the source trail and decide whether to cite with context, ask for methodology, clarify the denominator, add caveats, or avoid resharing the visual.

Data claims worth slowing down for.

Start where visual framing can change the next action. Rankings, percentages, poll results, maps, trendlines, model scores, benchmark charts, dashboards, screenshots, and infographic captions can change meaning when the source and denominator are visible.

Percentages and rankings

  • Claims where the base rate, sample size, or denominator changes the meaning.
  • Rankings that depend on sample, category definitions, sponsor context, or missing peers.
  • Comparisons where dates and geography are easy to lose.

Charts and dashboards

  • Line, bar, map, graph, benchmark, or dashboard screenshots with cropped axes or legends.
  • Visual claims where the axis scale, uncertainty interval, or missing baseline affects the takeaway.
  • Data screenshots that need the original report, table, or dashboard.

Polls and public numbers

  • Poll claims that depend on field dates, sample, and question wording.
  • Official-looking statistics without source links, sponsor notes, corrections, or methodology notes.
  • Viral data posts where a secondary article overstates the primary source.

What the check should surface before you rely on it.

The goal is not to certify a dataset, audit a model, provide data forensics, or perform statistical reanalysis. The goal is to slow the trust decision long enough to inspect the source trail, axis labels, time range, geography, denominator/base-rate context, methodology notes, sponsor context, uncertainty intervals, corrections, crop/context clues, caveats, confidence, and cautious share language.

Source and scope

  • Source links tied to the exact chart, statistic, poll number, or ranking.
  • Dates, geography, sample size, sponsor context, and category definitions preserved.
  • Caveats when the data source is stale, missing, or mismatched.

Visual framing

  • Axis labels, baselines, legends, units, and chart type visible.
  • Denominator/base-rate context before interpreting a percentage or trendline.
  • Uncertainty intervals, corrections, and primary-source limits separated from secondary-source framing.
  • Crop/context clues when a screenshot hides notes or neighboring data.

Cautious share language

  • Cite with source, date, geography, and denominator context.
  • Ask for the original report, table, dashboard, or methodology.
  • Avoid resharing when the chart is cropped or the source trail fails.

Related source-aware workflows.

Use the screenshot/image-caption page for image-carried data, economics page for markets and public finance, science page for climate data, technology/AI page for benchmark and model-score claims, research-study page for paper charts, press-release page for company data claims, quote-attribution page for sourced numerical quotes, news guide for article claims, source guide for citations, and hallucination guide for AI-generated statistics.

Install, then check one chart claim.

Open the download page, install the Chrome extension, and run a first-step check on one percentage, ranking, poll number, chart label, graph, benchmark, model score, map label, dashboard screenshot, or viral data claim before trusting, citing, or resharing it.

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