Regression Analysis

Tonya D. Lindsey, Ph.D.

Data Science Fellow
Institute of Governmental Studies (IGS)

Tonya D. Lindsey is a visiting scholar at the Institute of Governmental Studies and the project director of CRB Nexus: Where Policy Meets Research, an initiative of the California Research Bureau (CRB) at the California State Library. As project director of CRB Nexus, she is developing a community of practice space for California’s policy staff and public scholars. As a CRB senior researcher she uses her expertise in research methods to analyze a wide variety of policy questions at the request of legislators, the governor’s office, and their staff. She received her PhD in sociology...

Tracking Urban Expansion Through Satellite Imagery

December 12, 2023
Leïla Njee Bugha
by Leïla Njee Bugha. Among its many uses, remote sensing can prove especially useful to document changes and trends from eras or settings, where traditional sources are either inexistent or infrequently collected. This is the case when one wants to study urban expansion in sub-Saharan countries over the past 20 years. To further remedy the lack of data on land cover uses from earlier time periods, classification methods can be used as well. Using easily accessible satellite imagery from Google Earth Engine, I provide here an example combining remote sensing with classification to detect changes in the land cover in Nigeria since 2000 due to urban expansion.

From Asking Causal Questions to Making Causal Inference

December 5, 2023
Lauren Liao
by Lauren Liao. What is causality and how do we ask causal questions? It may seem like a difficult and foreign concept, but fear not, I will guide you through the basic concepts in this blog post. We will start from how to ask causal questions then more formally address how to answer these questions. You may find causality more approachable than you think. It follows the same ideas as presented by the scientific method of rigorously testing how interventions produce different outcomes in a controlled environment.

Using Forest Plots to Report Regression Estimates: A Useful Data Visualization Technique

October 17, 2023
Sharon Green
by Sharon Green. Regression models help us understand relationships between two or more variables. In many cases, results are summarized in tables that present coefficients, standard errors, and p-values. Reading these can be a slog. Figures such as forest plots can help us communicate results more effectively and may lead to a better understanding of the data. This blog post is a tutorial on two different approaches to creating high-quality and reproducible forest plots, one using ggplot2 and one using the forestplot package.

James Hall

Consultant
Department of Statistics

James Hall is a graduate student in the Statistics MA program at University of California, Berkeley. He is a husband and father to three awesome kids. Originally from Baltimore, MD, James earned his bachelors in Mathematics at the United States Military Academy at West Point, NY in 2011, and served as a U.S. Army officer. He’s served as a leader at multiple levels within large organizations with a professional focus on visualizing and communicating complex analysis to decision makers. James’ experience and coursework give him expertise in navigating different statistical methods,...

Michael Ruiz

IUSE Research Team
Psychology

Michael earned his B.A.in Psychology from UC Berkeley and currently works as the manager of Professor Okonofua's Equity, Diversity, and Empathy Navigation Sciences Lab in the UC Berkeley Psychology department.

Aniket Gupta

Discovery Fellow
School of Information

I am a first year masters student at UC Berkeley school of Information majoring in Information Management and Systems with a focus on Data Science and ML. I like to build optimized yet simple and scalable solutions powered by data using emerging AI technologies.

Daniel Lobo

Computational Social Science Fellow
Sociology

Daniel Lobo is a PhD student in the Department of Sociology with an emphasis in Political Economy at UC Berkeley. He is broadly interested in how culture, or the unspoken “rules of the game,” reproduces inequality within a system of racial capitalism. At the individual level, he is interested in documenting and measuring the extent to which cultural capital and social capital enable or constrain opportunities for intergenerational mobility. At the organizational level, he is interested in documenting and measuring the extent to which culturally-based selection and promotion processes...

Aniket Kesari, Ph.D.

Former D-Lab Postdoc and Senior Data Science Fellow
Berkeley Law

Aniket Kesari was a postdoc and data science fellow at D-Lab. He is currently a research fellow at NYU’s Information Law Institute, and will join the faculty of Fordham Law School in 2023. His research focuses on law and data science, with particular interests in privacy, cybersecurity, and consumer protection.

Featured D-Lab Blog Post: Introducing “A Three-Step Guide to Training Computational Social Science Ph.D. Students for...

Reubén Pérez

Consultant
Sociology

Reubén Pérez is a Ph.D. student in the Department of Sociology at UC Berkeley, where his research focuses on the politics of ethnoracial data production in the context of Latin America and the Caribbean.