Applied Regression Analysis (BUS 41100)
This website is ONLY for Autumn 2020, the remote version of 41100. For course material from previous quarters, go here.
- Instructor: Max H. Farrell
- Office hours (over Zoom): Wednesday 4:30 – 6PM, Saturday 11:30AM – 1PM
- TA: Gustavo Gonzalez
- This website: for all slides, homework, and data sets
- Piazza for Q+A: your first stop for help
- Zoom: all lectures will be over zoom, links will be sent in advance to students, and recordings will be available
- No Canvas site
Before class starts:
- Homework Zero – To test your readiness for this course
- Get started on R before class: see Computing below
Any updates/changes will be listed here.
- Syllabus updated: version 1.2 has new course schedule, including the midterm!
- Syllabus updated again: version 1.3.1
- New version of homeworks 5 and 6 posted
These will be updated as we go along, so always download the latest version
Week 1: Introduction, Simple Linear Regression (SLR)
Week 2: Inference for SLR
Week 3: Finish SLR, Start Multiple Linear Regression (MLR)
Week 4: Multiple Linear Regression Part II
Week 5: MLR Pitfalls and Some Fixes, Clustered and Panel Data
Week 6: An Introduction to Time Series
Week 7: Logistic Regression
Week 8 and Week 9: Classification and Model Building 1
Homework 0 | No data required, no solutions available
Homework 1 | box plots, scatter plots, stock market
Homework 2 | Monte Carlo code | SMSA data
Homework 3 | teacher salaries, tractors
Homework 4 | pricing experiment, cheese, Census data
Homework 5 | newspapers, NSW+PSID, beef
Homework 6 | UK gas consumption, US gas price, crime, bike sharing, pricing experiment, Grunfeld
The default computing language for this course is R, is free (as in speech) and available from CRAN. Other languages (e.g. python, MATLAB, STATA, ...) are allowed. Examples in lecture, homework solutions, etc., will be in R.
Get started before class starts!
- A good introduction/tutorial to R is here.
- UCLA has a fantastic help page for R (and statistics/regression in general) with everything from installation/basic help, worked-through examples, books, and link to more resources.
- The University offers R workshops in the Research Computing Center, see schedule here and has e-books available here.
- The resources out there are continually changing, so you may find other options. Please let me know if you find something helpful that isn't listed here.