208780 | Linear Statistical Models

Spring 2022

Time: Mon & Fri 9.30am-11.00am at SCB4402

Instructor

Readings

LectureTopicReadingHomework
1 Introduction to regressionROS Ch.6
2 Linear regression with a single predictorROS Ch.7Ex 6.2, 6.3, 6.6, 7.7, 7.8
3 Fitting linear regressionROS Ch.8
4 Prediction and Bayesian inferenceROS Ch.9
5 Linear regression with multiple predictorsROS Ch.10Ex 8.9, 9.7, 10.6(a), 10.7
6 Model diagnostics and evaluationROS Ch.11
7 Cross validation and log transformationsROS Ch.11, 12
8 Comparing regression modelsROS Ch.12
9 Logistic regressionROS Ch.13, 14Ex 11.5, 12.6(a)-(c), 12.7(a)
10 Interactions, APD, diagnostics ROS Ch.14
11 Generalized linear modelsROS Ch.15
12 Basics of causal inferenceROS Ch.18
13 Causal inference with regressionROS Ch.19Ex 18.1, 18.2, 18.4(a), 18.5
14 Causal inference with observational dataROS Ch.20
15 Subclassification and propensity score matchingROS Ch.20
16 Instrumental variablesROS Ch.21.1-2
17 Regression discontinuityROS Ch.21.3Pdf and data
18 Difference-in-DifferencesROS Ch.21.4
19 Panel dataROS Ch.21.4
20 Synthetic control
21 Conformal prediction
22 Jackknife+, CV+, Quantile regression and classification