STA 102: Intro to Biostatistics

STA 102 is an introductory course in statistics and data science motivated by timely applications from the health sciences, biomedical research, and public health. Students will understand common statistical methods and their suitability in answering specific research questions of interest, conduct rigorous, reproducible analysis using R, interpret results in context and translating them to language accessible to allied health science researchers, and critique statistical usage in the field in order to evaluate data-based claims and decisions.


Course info

Lectures

All times listed are in US Eastern Time Zone.

Section 001      M/W 3:30 - 4:45p      Reuben-Cooke 130

Labs

Lab 01 (Glenn)      Th 12:00 - 1:15PM      Perkins LINK 087 (Classroom 3)

Lab 02 (Grace)      Th 1:45 - 3:00PM      Perkins LINK 087 (Classroom 3)

Lab 03 (Yibin)      Th 5:15 - 6:30PM      Perkins LINK 087 (Classroom 3)



Teaching team and office hours
Instructor Yue Jiang MF 1:30 - 2:30 PM Old Chem 207A or Zoom (both)
Teaching Assistant Alexandra Lawrence M 4-5PM; W 5-6PM See Sakai for Zoom
Teaching Assistant Ben Wallace T 10 - noon See Sakai for Zoom
Teaching Assistant Glenn Palmer W 10 - noon Old Chem 203B
Teaching Assistant Grace Zhao T 2:30 - 4:30PM Old Chem 203B
Teaching Assistant Yibin Zhang Th 10 - noon See Sakai for Zoom

Additional instructor office hours are available by appointment.

Texts and software

No textbooks are required for this course; all lecture notes will be posted to the class website, with recorded lecture videos posted to the Sakai page after each class meeting. R is the statistical software used in STA 102, with the free user interface R Studio being highly recommended. A free, helpful online resource for R is Wickham and Grolemund, R for Data Science. This course makes heavy use of the tidyverse, a collection of open source R packages.