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Interactive 3D/Hypothesis Testing
Significance Level
α = 0.05
0.010.20
Test Statistic
t = 1.80
-44
Tail Type
Results
p-value:0.0359
α threshold:0.05
Decision:Reject H₀
Error Types
Type I (α): Rejecting H₀ when it's actually true. The red tail area = false positive rate.
Type II (β): Failing to reject H₀ when it's false. Controlled by statistical power.
Try: Slide t near the critical line - watch the decision flip. Then switch to two-tailed to see how the critical region splits.

Hypothesis Testing - Interactive Visualization

Hypothesis testing formalizes how to distinguish signal from noise. You set α (false positive rate), compute a test statistic from data, and reject H₀ if it falls in the rejection region. The p-value is P(seeing this extreme a result | H₀ is true). This visualization makes the logic concrete: drag the test statistic, see the p-value shade in, and watch Type I and Type II errors visualized simultaneously.

  • Drag the test statistic to see p-value update in real time
  • Set significance level α and see rejection region shade
  • Switch between one-tailed and two-tailed tests
  • See Type I error (α) and Type II error (β) regions simultaneously
  • Understand what "p < 0.05" actually means geometrically

Part of the EngineersOfAI Interactive 3D - free interactive visualizations covering every major concept in machine learning and AI engineering. Hover any element for a plain-English explanation. No code required.