Readings

Handouts, chapter notes and supporting papers

The core text is James, Witten, Hastie and Tibshirani (2021), An Introduction to Statistical Learning, 2nd edition, free from statlearning.com in both R and Python editions. The material below supplements it rather than replacing it.

Chapter handouts and notes

File	Type	Size
big-data-in-economics.docx	DOCX	16 KB
causal-inference-vs-machince-learning.pdf	PDF	647 KB
ch10.txt	TXT	4 KB
ch2-statistical-learning.pdf	PDF	826 KB
ch8.html	HTML	945 KB
classification.pdf	PDF	2.1 MB
cross-validation-model-selection.pdf	PDF	1.1 MB
cv-boot.pdf	PDF	414 KB
dimension-reduction.txt	TXT	4 KB
introduction-to-islr.docx	DOCX	19 KB
introduction.pdf	PDF	3.9 MB
knn-r-code-training-vs-test.pdf	PDF	154 KB
linear-models-2015-islr.docx	DOCX	33 KB
linear-models-2017-islr.docx	DOCX	17 KB
linear-regression.pdf	PDF	1.6 MB
logistic-lda-qda-comparison-2.html	HTML	16 KB
logistic-lda-qda-comparison-alt.html	HTML	10 KB
logistic-lda-qda-comparison.html	HTML	12 KB
machine-learning-in-economics.docx	DOCX	18 KB
pc-analysis.txt	TXT	16 KB
r-intro.pdf	PDF	32 KB
statistical-learning-handoutch2.pdf	PDF	817 KB
statistical-learning.pdf	PDF	826 KB
topics-in-advanced-econometrics.docx	DOCX	40 KB
trees.pdf	PDF	411 KB
unsupervised-learning.pdf	PDF	1.3 MB
unsupervised.pdf	PDF	1.3 MB
week5solutions5-25.pdf	PDF	1.1 MB