Apply Statistical Learning Theory to Your Own Dataset

10 weeks · 0 milestones

Document the bias-variance trade-off, model selection using cross-validation, and hypothesis testing applied to a dataset you collected yourself — not a pre-built Kaggle dataset. Your write-up must explain your data collection methodology, the specific modelling decisions you made and why, and the statistical tests you ran to validate each decision. Using your own data is the proof standard: it means the analysis cannot be pre-generated from a known dataset. Proof: the write-up and dataset reviewed by a statistician or ML practitioner who asks 'what would your cross-validation results look like if you doubled the number of folds?' — you must answer using your specific data and analysis, not the general principle.

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