Warning: The following schedule is a tentative guideline and will be evolving to meet course needs up to and during the semester.In particular, the pace of the course will be adjusted so that we move as possible conditional on everyone “getting” the material.
Introduction to 6029 and R
- January 24 Intro to the course Deck 1
- January 31 Lab 1: Introduction to R, RStudio and knitr
- Lab document: html, [RMarkdown]
- Data: [gapminder.csv](data/gapminder.csv)
Foundations of Linear Regression
- February 7 Review, Matrix Form Deck 2
- February 14 Lab 2: Graphing and Data Manipulation
- Lab document: html
- Readings:
- Wickham, Hadley. 2010. ``A Layered Grammar of Graphics.’’ Journal of Computational and Graphical Statistics 19(1): 3-28. link here
- Problem Set 1 Assigned, Due Feb 25
Assumptions & Properties of the Linear Regression Model
February 21 Properties and Assumptions, Deck 3
February 28 February Break - No Class
March 7 Lab 3: Linear Regression, Matrices, and predicted Values
- Lab document: html
- Readings:
- Problem Set 2 Assigned, Due March 18
Inference and Interpretation of Linear Regression
March 14 Inference and Interpretation of Linear Regression Deck 4
March 21 Lab 4: Multivariate Linear Regression, and Predicted Values
March 28 Specification, Bias, and Transformations Deck 5
April 4 Spring Break - No Class
April 11 Lab 5 Loops and simulation
- Lab document: html
- Problem Set 3 Assigned, Due Apr 22
Special Topics
April 18 Lab 6: Binary Models and Data Wrangling
- Lab document: html
- Problem Set 4, Due Apr 28
April 25 Lab 7: Case Study
May 2-4 Final Project Consulting
May 9 Final presentation
Poster Presentation and Final Paper
- May 12 Poster Due
- May 21 Final Paper Due