Effect Sizes and Statistical Significance › What's Next
Michael BrenndoerferJanuary 8, 20261 min read
Machine Learning from ScratchAll chapters Part 2 of 9Hypothesis Testing
Effect Sizes and Statistical Significance › What's NextOne section · Sections in this chapter10 / 11 ↓
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Understanding effect sizes prepares you for the multiple comparisons problem. When you conduct many tests simultaneously, each with its own effect size estimate, error rates compound and require special correction methods. You'll learn:
- Why multiple testing inflates false positive rates
- Bonferroni correction and its limitations
- False Discovery Rate (FDR) control
- When and how to apply corrections
The final section ties all hypothesis testing concepts together with practical guidelines for analysis and reporting.