## Advanced Quantitative Methods

POL 50050 **PhD Quantitative Methods II**

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

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 |