Lectures

Source code for lectures available on github.

• Motivation   (Sep 8)
• Random Variables, Probability and Models   (Sep 10-13)
• Monte Carlo methods   (Sep 17-22)
• Testing (Part 1)   (Sep 22-27)
• Estimation   (Sep 29-Oct 4)
• Prediction   (Oct 4-6)
• Exploratory Data Analysis and Unsupervised Learning   (Oct 8-13)
• Regression in more detail (simple, logistic, multiple)   (Oct 20-27)
• Maximum Likelihood   (Oct 28)
• Model Selection with Cross-validation   (Nov 1-5)
• Linear Regression and Model Selection   (Nov 5-10)   Optional additional notes: information criteria  
• Resampling and the Bootstrap   (Nov 12-15)
• Multiple comparison   (Nov 22-24)
• ANOVA   (Nov 29-Dec 3)
• Random effects   (Dec 6-?)
• Regression Trees   (Dec 13)
• Random Forests   (Dec 15)