Slides
The slides used in class are published here as PDF, one deck per chapter.
Note
Some decks are shared on Microsoft Teams instead of being published here, when they contain figures from a textbook that cannot be redistributed. The chapter page says so explicitly when that is the case.
| Deck | Title | |
|---|---|---|
01_key_concepts |
Key concepts of data analysis | |
02_describing_visualizing |
Describing and visualizing the data | |
03_probability |
Probability for data analysis | |
04_association |
Association between variables | |
05_distributions |
Data distributions | |
06_statistical_inference |
Statistical inference: sampling, confidence intervals, bootstrap, hypothesis testing | TBA |
07_comparing_groups |
Statistical tests in practice: comparing groups, effect size, multiple tests | TBA |
08_linear_regression |
Linear regression | TBA |
09_logistic_regression |
Logistic regression | TBA |
10_extending_regression |
Extending regression models: interactions, polynomial terms, multinomial regression | TBA |
11_causal_analysis |
Causal analysis and experimental design | TBA |
13_predictive_analysis |
Introduction to predictive analysis: empirical risk, baselines, splits, cross-validation | TBA |
14_regression_for_prediction |
Regression for prediction: overfitting, regularization, the scikit-learn workflow | TBA |
15_classification |
Classification: metrics, KNN, logistic regression as a predictor | TBA |
16_generative_classifiers |
Generative classifiers: QDA, LDA, naive Bayes | TBA |
17_data_representation |
Data representation and clustering | TBA |
18_clustering |
Data representation and clustering | TBA |
19_density_estimation |
Density estimation | TBA |
20_pca |
Dimensionality reduction: principal component analysis | TBA |