Event box
A Slower Introduction to R: Session 1: Do math Online
About the series
This session is the first in a 7-session workshop series on R, A Slower Introduction to R. The series is designed for UCSF researchers who intend to begin using R in their research. The series is intended to be a (relatively) slow-paced introduction to R. It does not assume any prior exposure to R or computer programming.
The series has been designed to help learners approach common data-related tasks, and will draw on data examples from the health sciences (including public health and medicine).
Each session (scheduled for 1.5 hours, but we may finish earlier on occasion) will involve short mini lectures, interspersed with hands-on exercises.
Registration for each session is required, using UCSF MyAccess.
We plan to host intermediate-level workshops on R in Spring 2025 (dates and details pending).
About the session
Each session is titled in the form of a "How can I..." question. This first session is titled "How can I do math?" and will cover:
- RStudio's panes
- the RStudio console
- mathematical operators
- mathematical functions
- object assignment
Please install R and RStudio prior to attendance. Instructions will be sent out via email prior to the session.
Please watch the orientation video prior to attendance. A link will be sent out via email prior to the session.
About the instructor
The instructor, Yea-Hung Chen, PhD, MS, has 10 years of experience teaching R to the UCSF community. He designed and taught UCSF's first-ever R course (Biostat 213) and taught the introductory biostatistics course for UCSF's MS in Global Health program (GHS 207).
Accessibility statement
Slides will be available on the Course Learning Environment at least 24 hours prior to each session. Learners are welcome to use recording or closed-captioning features embedded in the Zoom platform. To request reasonable accommodation for this session, please email the instructor (yea-hung.chen@ucsf.edu) as soon as possible.
- Date:
- Friday, Jan 24 2025
- Time:
- 10:00am - 11:30am
- Time Zone:
- Pacific Time - US & Canada (change)
- Campus:
- Online
- Online:
- This is an online event. Event URL will be sent via registration email.
- Categories:
- Data Science