Litterature

Rawlings, J.O., Pantula, S.G., Dickey, D.A.: Applied Regression Analysis - A Research Tool, 2ed, Springer

Overview

When	What	Material
1: Mon 23/3, 13.15-15.00, Zoom 2: Wed 25/3, 8.15-10.00, Zoom	Lecture 1+2: Review of simple linear regression as a special case of multiple linear regression, with and without matrices. Linear models, basic assumptions (normality, homoscedasticity, linearity, independence). Least squares estimation, Mean, variance and distributions of least squares estimators. Prediction. Confidence intervals, Prediction intervals. Basic residual analysis. Log-transformation.	Rawlings Ch. 1.1-1.3, 1.5, 1.9, Ch. 2, Ch. 3, Ch. 12 Slides: lecture_0_vt20.pdf; lecture_1_and_2_vt20.pdf R-code: simple_linear_icecream.R; simple_linear_cod.R; (Link fixed!) transformed_linear_cod.R Data: icecream.RData; cod.RData Video: Lecture videos: linear regression
Mon 30/3, 13.15-15.00, Zoom	Lecture 3: (a) Multiple linear regression: critical requirements; ill-ranked design matrices, lack of invertibility. Interaction. (b) Categorical variables	Rawlings Ch. 3, 6.5 Slides: lecture_3a_vt20.pdf lecture_3b_vt20.pdf R-code: multiple_elasticity.R categorical_cabbage.R Data: elasticity3d.rda Video: Lecture videos: linear regression
Wed 1/4, 8.15-10.00, Zoom	Lecture 4: Testing: t-test, Analysis of variance: variability decomposition. Global F-test. ANOVA tables. Partial F-test.	Rawlings Ch. 9, Ch. 4 Slides: lecture_4_vt20.pdf R-code: categorical_cabbage_parametertest.R (bugfix 1/4) Video: Lecture videos: linear regression
Mon 6/4, 13.15-15.00, Zoom	Lecture 5: Regression diagnostics: outliers w.r.t. X (leverage), distribution of residuals, standardised and studentised residuals; graphical tools for residual analysis. Influential observations (Cook's distance, DFBETAS)	Rawlings Ch. 10-11 Slides: lecture_5_vt20.pdf R-code: influential_pike.R Data: pike.rda Video: Lecture videos: linear regression
Tue 7/4, 8.15-10.00, Zoom	Lecture 6: R-squared, Adjusted-R-squared, AIC & BIC, automatic selection methods	Rawlings Ch. 7 Slides: lecture_6_vt20.pdf R-code: categorical_cabbage_variableselection.R Video: Lecture videos: linear regression
Mon 27/4, 15.15-17.00, Zoom	Lecture 7: Wrapping up linear regression and starting on module 2. Logistic regression (q.v.)