Johan A. Elkink
teaching

Advanced Quantitative Methods

POL 50050 PhD Quantitative Methods II

Tuesday, 9-11 am, room G317, Newman Building (building 36 on the campus map).

Syllabus

While the statistical package R is the software used on slides, students can use any package of choice. A booklet with commands in R, Stata, and SPSS will be made available. R can be downloaded for free here. A handy overview of R regression commands can be found here: reference card for regression. A more general one for R is here: short reference card.

A booklet is in production with all relevant commands for the course in a number of different statistical packages, with an early draft here: Statistical Software Guide for Introductory Econometrics. Since we are actively working on this booklet, any feedback would be greatly appreciated.

For R users, please make sure to install the following packages prior to the second lecture of the course:
faraway, arm, lmtest, tseries, ape, MASS, plm, and pcse.

Here is an interesting list of statistics blogs.

It is generally advisable to bring electronic copies of slides and lecture notes (where applicable) to the class. I would recommend not to print the slides, however, since these are large files. There is also WiFi access available in-class.

Data can be found on the teaching data page.

Lecture 1 Mathematics review slides notes
Lecture 2 Statistical estimators slides notes
Lecture 3 Ordinary Least Squares slides notes homework
Lecture 4 Hypothesis testing slides
Lecture 5 Regression diagnostics slides homework
Lecture 6 Time-series analysis slides
Lecture 7 Causal inference slides notes homework
Lecture 8 Maximum Likelihood slides
Lecture 9 Limited dependent variables I slides homework
Lecture 10 Limited dependent variables II (continued)
Lecture 11 Bootstrap and simulation slides notes
Lecture 12 Multilevel data slides homework