Notice: Starting in spring 2016, the official class number is 220:222. Class 222 will be a required course for econ major and a prerequisite for econ 322 starting in fall 2016. Class 222 can also be used as a prerequisite for higher level quantitative class such as Applied Data Mining (220:422).
Foundations of Econometrics 222, Fall 2016
FE 222 is a computation oriented class where students learn modern statistical models using powerful software such as R and Stata. The contents of this class is simlar to the traditional mathematical statistics course. However, the focus is on the understanding of Probability Theory and Inferential Statistics using visualization and simulation methods. Starting in Fall 2016, the class integrates a wonderful learning web site DataCamp into the curriculum; in addition to learning from the class material, students have the opportunity to take courses to enhance their data analysis and programming skills in R and Python at DataCamp and earn certificates. For complete information, visit https://www.datacamp.com/.
Foundations of Econometrics 367, Fall 2015
Required Textbook (springer link via library)
Instruction: you can have access to the required textbook directly at school with Rutgers internet service or you can approach the book site by logging into library web site using your NetID and Password first while you are off-campus. Please feel to contact me if you have any questions.
- Handout #1 (Stata Code)
- Handout #2 (Stata Code)
- Handout #3
- Handout #4 (Stata Code)
- Handout #5 (Stata Code)
- Handout #6 (Stata Code)
- Handout #7 (Stata Code)
- Handout #8 (Stata Code)
- the rest (Diagnostic checks on LR & Bayesian statistics) is coming soon!
Statistical computing software suggestion: Learn how to write your own estimators using matrix oriented language such as Matlab, R or SAS (IML module) plus be familiar with a canned package such as EViews or Stata.
Foundations and Applications of Econometrics 368, Spring 2015
- Handout #1 (R Code)
- Handout #2 (R Code)
- Handout #3 (R Code)
- Handout #3 (supplement: probability theory)
- Handout #4 (R Code)
- Handout #5 (R Code)
- Handout #6 (R Code)
*Homework Assignments and Solutions can be found on sakai