Regression Analysis

Megumi Tanaka

Data Science for Social Justice Fellow 2024
School of Journalism

I'm currently a graduate student in the AS&T program and the School of Journalism, conducting research in the field of AI ethics education. I'm interested in the intersection of data science, journalism and education!

Christian Caballero

Data Science Fellow 2024-2025
Political Science

Christian Caballero is a Political Science PhD student at the University of California, Berkeley. His research focuses on American politics and political behavior. In particular, he studies the ways in which social networks influence processes of political persuasion and democratic deliberation, as well as how political ideologies develop within subcultures.

He holds a B.A. in Politics and Sociology from New York University and an M.A. in Political Science from the University of California, Berkeley.

Sahiba Chopra

Data Science Fellow 2024-2025
Haas

I'm a PhD student in the Management and Organizations (Macro) group at Berkeley Haas. I have a diverse professional background, primarily as a data scientist across numerous industries, including fintech, cleantech, and media. I hold a BA in Economics from the University of Maryland, an MS in Applied Economics from the University of San Francisco, and an MS in Business Administration from UC Berkeley.

My research focuses on the intersection of inequality, technology, and the labor market. I am particularly interested in understanding how to reduce inequality in...

Mingyu Yuan

Data Science for Social Justice Senior Fellow 2024
Linguistics

I am a Ph.D. candidate in Linguistics, with a focus on phonetics and phonology, specifically speech production in neuro-atypical populations. I use methods from Natural Language Processing in my day-to-day research.

Violet Davis

Data Science for Social Justice Senior Fellow 2024
MIDS

I am a Masters student studying Data Science with the School of Information. My research involves computational social science projects focused on social justice and equity.

Skyler Yumeng Chen

Data Science for Social Justice Fellow 2024
Haas School of Business

Skyler is a Ph.D. student in Behavioral Marketing at the Haas School of Business. Her research centers on consumer behavior and judgment and decision-making, with a keen interest in both experimental methods and data science techniques. She holds a B.A. in Economics and a B.S. in Data Science from New York University Shanghai.

Grace Hu

Data Science for Social Justice Fellow 2024
Bioengineering

Grace is a 3rd year Bioengineering PhD candidate in the joint UC Berkeley-UCSF Graduate Program. Her research lies at the nexus of computational design and 3D-bioprinting to advance tissue engineering for regenerative medicine. She previously studied Materials Science and Engineering (B.S.) and Computer Science (M.S.) at Stanford University, where she investigated printable batteries to power an ultra-affordable scanning electron microscope and explored computer science education research by developing AI models to augment teaching ability.

In her free time she...

A Basic Introduction to Hierarchical Linear Modeling

March 4, 2024
by Mingfeng Xue. Hierarchical Linear Modeling (HLM) is an extension of linear models, which offers an approach to analyzing data structures with nested levels. This blog elucidates HLM's significance over traditional linear regression models, particularly in handling clustered data and multilevel predictors. Illustrated with an example from educational research, the blog demonstrates model implementation and interpretation steps. It showcases how HLM accommodates both independent variables from different levels and hierarchical structure data, providing insights into their impacts on the outcome variable. Recommended resources further aid readers in mastering HLM techniques.

Creating the Ultimate Sweet

January 30, 2024
by Emma Turtelboom. What is the best Halloween candy? In this blog post, we will identify attributes of popular sweets and create a model to understand how these attributes influence the popularity of the sweet. We’ll discuss alternative model approaches and potential drawbacks, as well as caveats to interpreting the predictions of our model.

Reine Ngnonsse

IUSE Undergraduate Advisory Board
Genetics and Plant Biology

Reine Ngnonsse, an enthusiast for math and technology, delved into tutoring math at a community college through the EOPs program. At UC Berkeley, while pursuing Genetics and Plant Biology, She explored R programming in a CRISPR project. As an intern at Health Career Connection, Reine expanded coding skills in Python, R, and Tableau, igniting a passion for programming. With exposure to Python and Javascript, she can't wait to merge mathematical prowess with coding finesse for innovative solutions.