STA 323 & 523

A practical introduction to statistical programming focusing on the R programming language. Students will engage with the programming challenges inherent in the various stages of modern statistical analyses including everything from data collection/aggregation/cleaning to visualization and exploratory analysis to statistical model building and evaluation. This course places an emphasis on modern approaches/best practices for programming including: source control, collaborative coding, literate and reproducible programming, and distributed and multicore computing.


Welcome to STA 323 - Statistical Computing and STA 523 - Programming for Statistical Science, a joint course for undergraduate and graduate students. This is the course website for spring 2021. Much of the information you will need throughout the semester can be found here. Please read the syllabus thoroughly, and take a look at the course schedule for topics covered and when assessments are assigned.


Course meetings

Zoom links for all meetings and their recordings can be found in Sakai.

Lecture

  • In-person: Old Chemistry 116, Wed and Fri 10:15am - 11:30am

  • Virtual: Wed and Fri 10:15am - 11:30am

Lab

  • Virtual: Mon 10:15am - 11:30am

Teaching team and office hours

Zoom links for all office hours can be found in Sakai.

Instructor
Shawn Santo        Mon 8:00pm - 9:00pm, Thu 12:30pm - 1:30pm

Graduate Teaching Assistants
Quinn Frank   Wed 11:30am - 1:30pm
Pierre Gardan   Tue 10:00am - 11:00am, 6:00pm - 7:00pm
Sarah Mansfield   Thu 10:00am - 11:00am, Fri 4:00pm - 5:00pm


All times listed are in Eastern Time.