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with Keith McCormick
Gain insights to help improve your machine learning models and statistical analyses.
Prediction, causation, and statistical inference
Lady tasting tea
Why causation matters in a business setting
What is a causal model?
Skepticism about data: Truman 1948 Election Poll
Skepticism about results: Is that really the best predictor?
Skepticism about causes: Is X really causing Y?
What is a strong correlation?
Pearson on correlation and causation
Correlation and regression
Challenge: What is causing what?
Solution: What is causing what?
Using probability to measure uncertainty
p-value review
Hypothesis testing checklist
Taleb on normality, mediocristan, and extremistan
Challenge: Evaluate significant finding
Solution: Evaluate significant finding
What are induction and deduction?
Hume on induction
Popper on induction and falsification
Taleb on induction
Counterfactuals: Pearl on induction and causality
Data mining vs. data dredging
Train/Test: What can go wrong?
A/B testing during the evaluation phase
The Two Cultures
Explain vs. predict
Comparing CRISP-DM and the scientific method
Applying the two methods at work
Review