Are you an education researcher that is interested in learning R for data analysis purposes? Apply now to join us for the Spring 2019 QUBES Faculty Mentoring Network (FMN).
Participants in this FMN will focus on learning how to use R, including the basics of how to get started in R, exploratory data analysis, and basic statistical techniques such as t-tests, ANOVAs, and linear regression. Accepted applicants will use R to analyze their own data set. While doing this, they will participate in 1-hour biweekly virtual sessions to collaborate with and support others in the network and receive mentoring.
Applications are due December 7, 2018. Accepted applicants will be notified by December 14, 2018.
Space is limited, and the network is launching soon, so apply now!
Description: QUBES (http://qubeshub.org) is working with education researchers who are interested in learning R to apply it to their research. Participating researchers should have their own data set that they would like to analyze using R.
Dates & Location:
The virtual kick-off will be held in mid-January, 2019 (date and time TBD). The FMN will continue online to support the learning and application of R to your own data during the Spring 2019 semester.
How to Apply:
Applications are due December 7. You can follow this link to view the application form. Accepted applicants will be notified by December 15. Space is limited, only 15 participants will be selected.
To qualify, participants must have a data set that they can analyze during the Spring 2019 semester. Participants must also be able to commit ~1 hour biweekly for working with mentors and collaborating with other participants around the use of R. Additional time outside of these discussions will be required for independent work on practice exercises in R or for data analysis on their own data set.
Benefits of Participation:
**Sharing of learning tools and materials for using R for data science.
**Online support throughout the process of learning R.
**Access to peer mentors on effective tips and strategies for data analysis in R in small group virtual meetings every two weeks
If you have questions, please feel free to contact Melissa Aikens at firstname.lastname@example.org or Drew LaMar at email@example.com.