A career changer, I completed my Master of Science in Statistics from California State University East Bay in May 2023. Following graduation, I worked as a Data Scientist providing statistical support and expertise to process engineers in Intel’s leading developmental fab. I’m also a board member of the Data Science Learning Community, widely known in the data community as organizers of the Tidy Tuesday weekly social data project.
You can find me elsewhere at:
Cascadia R Conference 2024 talk: Learning Together at the Data Science Learning Community
Recording | Slide Presentation | Abstract
- Cascadia R Conf 2024, June 22, 2024. Talk Track: OuR journeys in community & collaboration
- Description: Since 2017, the Data Science Learning Community (DSLC, fka the R4DS Online Learning Community) has organized weekly book clubs to help data science learners and practitioners read and discuss data science books in safe, nurturing, small-group cohorts. We also support one another by asking and answering programming questions in our Slack help channels. I discuss how we keep our Slack community friendly and inclusive, and various way to participate in the community.
posit::conf(2023) talk: How the R4DS Online Learning Community Made Me a Better Student
Recording | Slide Presentation | GitHub Repo | Related Blog Post
- Posit Conference, September 20, 2023. Talk Track: Developing your skillset; building your career. Session Code: TALK-1110
- Description: Through my participation in R4DS, I advanced my R and data science skills, making me a better student than I otherwise would have been through just my studies. Along with helping to improve my programming skills, R4DS connected me with scholarships, mentorship, and other opportunities. I discuss the benefits students gain by joining the community.
Data Visualization
GitHub Repo | Tableau | R Pub Notebooks
- STAT 651 Data Visualization, California State University East Bay, Fall 2022
Practicality of Using Transformations in Multiple Linear Regression
GitHub Repo | Slide Presentation | Video Presentation
- Final Project for STAT 694 Applied Research in Statistics & Biostatistics, California State University East Bay, Fall 2022
- Compared the multiple linear regression (MLR) model with the inverse transformation dependent response variable to see how much prediction power is lost by not using a transformed response variable to fit a MLR model, and whether it is worth the inability to easily explain your model when using a transformed response variable.
Gender Wage Inequality in STEM
GitHub Repo | Slide Presentation | Video Presentation
- Co-authors: Sara Hatter and Ken Dinh Vu
- Final Project for STAT 632 Linear and Logistic Regression, California State University East Bay, Spring 2022
- Explored the data for STEM college majors to find associations that influence median wages and create a predictive model for median wages.