Researchers are producing more data than ever before. Since so much data could never be analyzed by hand, automation is essential. One crucial skill for researchers to learn is how to use coding to automate repetitive tasks like data cleaning, analysis and visualization.
To help with that, the popular Coding and Cookies workshops, co-hosted by the Colorado State University Libraries and the Graybill Statistics and Data Science Laboratory, are back – although it’s a bring-your-own-cookies situation this semester.
The Coding and Cookies series teaches the basics of how to use R and RStudio to make research more efficient, reliable and reproducible.
The workshops have been adapted to support online learning. The new format will be a flipped classroom approach: Learners will watch a video prior to a session and an online, live workshop will be used to review key concepts and work through additional problems. Learning materials will be publicly available online. If sessions are full, interested students are encouraged to watch the videos and get in touch with the instructors with follow-up questions.
Sessions will be led by experienced statistics graduate students and facilitated by Mara Sedlins, Ph.D., data management specialist at the CSU Libraries, and Julia Sharp, associate professor of statistics and director of the Graybill Statistics and Data Science Laboratory.
Fall workshops and schedule
Registration is required, and capped at 10 attendees to ensure learners get the attention they need in an online environment. If researchers are new to the R programming language or RStudio, they are encouraged to sign up for the first session, R Basics.
• Sept. 8, 10-11 a.m.
• Sept. 22, 10-11 a.m.
Tidy Data in R
• Oct. 13, 10-11 a.m.
Data Visualization using ggplot2
• Oct. 27, 10-11 a.m.
Reproducible Reports using R Markdown
• Nov. 10, 10-11 a.m.
More support available
For more support with data management, Sedlins provides consultations by appointment. Contact her at Mara.Sedlins@colostate.edu.
For more support with statistics, data science, and statistical computing, request a consultation with the Graybill Statistics and Data Science Laboratory.