Course overview
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, and data visualization, and effective communication of 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. No statistical or computing background is necessary. Not open to students who have taken a 100-level Statistical Science course, Statistical Science 210, or a Statistical Science course numbered 300 or above.
Class meetings
| Meeting | Location | Time |
|---|---|---|
| Lecture | Biological Sciences 111 | Tue & Thur 11:45 am - 1:00 pm |
| Lab 01 | Perkins LINK 071 (Classroom 5) | Mon 8:30 - 9:45 am |
| Lab 02 | Perkins LINK 071 (Classroom 5) | Mon 10:05 - 11:20 am |
| Lab 03 | Perkins LINK 071 (Classroom 5) | Mon 11:45 am - 1:00 pm |
| Lab 04 | Perkins LINK 087 (Classroom 3) | Mon 1:25 - 2:40 pm |
| Lab 05 | Perkins LINK 087 (Classroom 3) | Mon 3:05 - 4:20 pm |
| Lab 06 | Perkins LINK 087 (Classroom 3) | Mon 4:40 - 5:55 pm |
| Lab 07 | Old Chemistry 003 | Mon 4:40 - 5:55 pm |
| Lab 11 | Perkins LINK 071 (Classroom 5) | Mon 1:25 - 2:40 pm |