Syllabus Map
- Study map: Syllabus Study Map
Core Idea
- Hypothesis tests assess whether observed effects are likely under a null hypothesis.
- Confidence intervals quantify uncertainty in estimated quantities.
Practical Notes
Report uncertainty, not only point estimates.
- Include intervals or repeated-run variability in comparisons.
Why This Matters for ML
- Confidence intervals and significance testing contextualize model comparison results.
- They help separate real performance gains from random variation.
- Ablation and benchmark claims are stronger when paired with uncertainty estimates.
- Inference basics improve rigor in experimental ML reporting.