STA 199: Intro to Data Science
Intro to data science and statistical thinking. Learn to explore, visualize,and analyze data to understand natural phenomena, investigate patterns, model outcomes,and make predictions, and do so in a reproducible and shareable manner. Gain experience in data wrangling and munging, exploratory data analysis, predictive modeling, data visualization, and effectively communicating results. Work on problems and case studies inspired by and based on real-world questions and data. The course will focus on the R statistical computing language.
|Lecture||All Students||Mon and Wed 10:15a - 11:30a|
|Labs||Lab 05||Thu 8:30a - 9:45a|
|Lab 06||Thu 3:30p - 4:45p|
|Lab 07||Thu 5:15p - 6:30p|
Join live lectures, labs, and office hours using the Zoom links in Sakai.
Click on the schedule tab to keep up with all activities and assignments.
Teaching team and office hours
|Instructor||Prof. Maria Tackett||Mon 1p - 2p|
|TAs||Salvador Arellano||Tue 10a - 12p|
|Morris Greenberg||Fri 12p - 1p|
|Caroline Levenson||Wed 2p - 4p|
|Ezinne Nwankwo||Mon & Wed 8:30a - 9:30a|
|Matty Pahren||Tue & Thu 2p - 3p|
|Felipe Ossa||Wed & Fri 5p - 6p|
|R Support TA||George Lindner||Tue 5p - 6p & Fri 3:30p - 4:30p|
Click on the Help tab for information about office hours, Piazza, and othe resources.