When	What	Material
Mon 27/4, 15.15-17.00, Zoom.	Lecture 7: Wrap up module 1. Linear regression. Start on binary data, Bernoulli and binomial distributions, odds ratios and Logistic regression, Maximum likelihood estimation, Newton-Raphson, properties,	Agresti Ch. 1, sec 1.2.1, sec 2.3, etc Slides: lecture_7_vt20.pdf R-code: polluting_particles.R (bug fixed 27/4) Data: exampledata.rda pm10.rda Video: See Lecture videos: logistic regression
Tue 28/4, 8.15-10.00, Zoom	Lecture 8: deviance and likelihood ratio tests. Residuals and model validation in logistic regression. Akaike (again), Pseudo-R2.	Agresti: 1.3.1, 1.4.1, 2.3.1-2.3.3; several topics scattered in Ch. 4, particularly sections 4.1-4.2. Slides: lecture_8_vt20.pdf R-code: polluting_particles_resids.R (bug fixed 28/4) Data: pm10.rda Video: See Lecture videos: logistic regression
Mon 4/5, 13.15-15.00, Zoom	Lecture 9: Goodness-of-fit. Confusion matrix, sensitivity, specificity, ROC-curve and Area Under Curve, Hosmer-Lemeshow test.	Slides: lecture_9_vt20.pdf R-code: polluting_particles_GOF.R Data: pm10.rda Video: See Lecture videos: logistic regression
Wed 6/5, 8.15-10.00, Zoom	Lecture 10: Wrap up logistic regression and start on Lecture 10 - 12: Other regressions