Check the story a chart tells
A rising line does not explain its cause. Test sample claims about counts, percentages and performance against the underlying data.
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Separate claims from evidence
Fictional support data: 8 of 10 requests were completed in week one and 12 of 20 in week two. Staffing and request difficulty also changed. Classify what the displayed sample supports, then inspect the explanation.
- Checked
- 0 of 3
- Matches the sample
- 0 of 3
Use the sample evidence: supported means it backs the claim; uncertain means it does not settle the claim; contradicted means it conflicts with the claim. These are fictional examples.
For the moments like this.
A presentation shows a rising line and says that a recent change improved performance. You want to understand whether the data supports that conclusion or merely shows two things happening together. Inspect a small fictional set of counts and conditions, then decide which claims can safely appear in the accompanying explanation.
What becomes possible
Compare three claims with fictional request counts and completion rates. Check the arithmetic, then decide whether the records explain why the result changed.
Put this to work.
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Sources, capability notes and how this example works
This local experience uses authored sample content and deterministic controls. Changing an input updates the example; no model runs, outside records are checked, or real-world actions are performed. Use the sources for the underlying AI capabilities and audience context, and the human check above when you apply the idea.
Data analysis with ChatGPT ↗Current capability documentation; analysis depends on the supplied records and needs review. Accessed September 11, 2026.
Research checked September 11, 2026. Access to specific AI features depends on your account, plan and region. Sample amounts, timings, scores and feedback illustrate the method rather than claim measured outcomes.