R for Data Science: Part 3

Instructors:

Dillon Niederhut

Dillon Niederhut was research associate of the D-Lab services team, where he led development of the python and R curricula, and provides programming support for data collection and analysis. He received a PhD in the anthropology department in spring 2016, where he used high field MRI to study brain evolution, tract-based statistics to study human development, and natural language processing to study emergence and diversification. Prior to working for the D-Lab, Dillon led the community outreach efforts of Berkeley's Graduate Assembly.

Read more about Dillon Niederhut

When & Where

Date:

Fri, October 30, 2015 - 1:00 PM to 3:00 PM

Location:

Convening Room

Description

Type:

Workshop

The R for Data Science workshop series is a four part course, designed to take novices in the R language for statistical computing and produce programmers who are competent in finding, displaying, analyzing, and publishing data in R.

Day 3 (analyzing data)

Students will be introduced to the principles behind the grammar of graphics and the general linear model. Students will understand the implementation of plotting in R. Students will be able to explore, summarize, and analyze data using R's implementation of exploratory and inferential data analysis.

Want to learn more? Check out the remaining R for Data Science workshops:

R for Data Science: Part 4

Link:

Course materials

Keyword:

Details

Training Host:

D-Lab

D-lab Facilitator:

Patty Frontiera

Participant Technology Requirement:

Laptop required with R installed; students are expected to know the basics of R and tidy data before attending.