Welcome to STA 490/690, Spring 2021!
The readings/preparations for the class can be found on the course webpage.
Class time: Friday 10am - 12:30pm EDT
Class and Office Hours Meeting ID: 942 6221 2181
Passcode: Has been emailed to you!
The course webpage is meant to be a place that you can access all the relevant course materials, such as readings, slides, etc.
The syllabus is a comprehensive place regarding expectations for the course.
Piazza
Piazza will be used as a group forum for all questions for the course as well as announcements.
Github
Github will be used for all homework submissions and group projects. You will be expected to have group repository for this class that is organized by your group leader.
Required readings for the course will be posted on the course webpage.
Before starting the course for the fall semester, I would highly recommend review the pre-req material for the course on the syllabus. Given the shortened semester, please make sure that you are 100 percent comfortable with the pre-req material before taking STA 490/690. If you have any questions regarding this, please reach out to me as soon as possible. Specifically, please be sure to review STA 360/602 if you feel rusty with any components from this course. If you have not learned maximum likelihood estimation (MLE), I would ask that you learn this before the first day of class.
R programming will be fundamental to this course, please be sure to refresh this if you're not comfortable with R.
- Intro to R, Part I
- Intro to R, Part II
- Intro to R, Part III
- Intro to R, Part IV
- Intro to R, Part V
- Intro to R, Videos
- Reference Text: http://shop.oreilly.com/product/9780596809164.do (The R Cookbook, not to be confused with the one for graphics).
Github will be required for the course. Please learn this before the first day of class if you're not already familiar as this is where the course resources are located.
Resources: