Qualitative Analysis

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...

Hellina Hailu Nigatu

Data Science for Social Justice Senior Fellow 2024
Electrical Engineering and Computer Science (EECS)

I am a PhD student at UC Berkeley in the EECS department co-advised by Prof. Sarah Chasins and Prof. John Canny. My research interest broadly lies in the intersection of AI and HCI, with a focus on making usable AI tools accessible to end users.

I am currently looking into making NLP tools usable and accessible for low-resourced languages. I am also interested in the impact of AI on society, specifically in how it affects Global Majority countries and communities. Outside of research, I like to read books, make and drink traditional Ethiopian coffee, knit,...

Minding the Gaps: Pay Equity in California

July 9, 2024
Tonya D. Lindsey, Ph.D.
by Tonya D. Lindsey, Ph.D. The gender pay gap continues to reflect that, on average, men outearn women. California is among the states with the smallest pay gaps (outpacing the national number at 13%) and is unique in that it enacted legislation aimed at eliminating pay gaps by sex and race categories. This blog post reflects on California’s pay gap as students study it in an undergraduate social statistics course. Independent variables indicate three theoretical frameworks: 1) human capital, 2) occupational segregation, and 3) discrimination. While the work students do is rigorous using a representative sample of full-time year-round California workers, there remains work to be done and caveats to the data and analyses.

Berkeley FSRDC Fundamentals

January 31, 2024, 11:00am
Interested in restricted Census or partnering RDC agency (AHRQ, BLS, BEA, NCHS) data use? This one-hour introductory workshop will provide an overview of the Berkeley Federal Statistical Research Data Center, with no prior experience assumed. Attendees will learn about the national RDC network, how to access information online about restricted Census data, and how to navigate proposal development.

US Census Bureau Restricted-Access Research Data Center (FSRDC) Info Session

April 24, 2024, 11:00am
Interested in restricted Census or partnering RDC agency (AHRQ, BLS, BEA, NCHS) data use? This one-hour introductory workshop will provide an overview of the Berkeley Federal Statistical Research Data Center, with no prior experience assumed. Attendees will learn about the national RDC network, how to access information online about restricted Census data, and how to navigate proposal development.

QDA Campus License Focus Group

October 12, 2023, 12:00pm
Calling All Qualitative & Mixed-Methods Researchers at UC Berkeley! Join the conversation on Qualitative Data Analysis (QDA) Campus Software License Options! Are you a researcher (undergraduate, graduate, or faculty/staff) at UC Berkeley who employs qualitative data, text analysis, or mixed-methods research approaches? If you rely on specialized software like Atlas.ti, NVivo, MaxQDA, Dedoose, or Otter.ai in your work, Research IT & D-Lab want your input to inform the future of qualitative research supports at UC Berkeley.

Survey Fundamentals

April 11, 2024, 3:00pm
This two-hour workshop offers a comprehensive introduction to designing and conducting survey studies. Tailored for beginners, it provides clear, step-by-step guidance complemented by concise examples, practical considerations, and useful support materials. Participants will learn the entire process, from formulating a research question to creating, administering, and analyzing surveys, as well as interpreting results and communicating their findings.

Survey Fundamentals

February 21, 2024, 1:00pm
This two-hour workshop offers a comprehensive introduction to designing and conducting survey studies. Tailored for beginners, it provides clear, step-by-step guidance complemented by concise examples, practical considerations, and useful support materials. Participants will learn the entire process, from formulating a research question to creating, administering, and analyzing surveys, as well as interpreting results and communicating their findings.

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.

Enhancing Research Transparency Inspired by Grounded Theory

April 30, 2024
Farnam Mohebi
by Farnam Mohebi. Grounded theory, a powerful tool for qualitative analysis, can enhance data science research by improving transparency and impact. Researchers can create a vivid record of their process by meticulously documenting the entire research journey, including the decisions they make and the corresponding rationale behind them, from initial data exploration to developing and refining theories. Embracing grounded theory principles, such as iterative coding and constant comparison, can help data scientists build robust, data-driven theories while ensuring transparency throughout the research process. This approach makes research more replicable and understandable and invites others to engage with the work, fostering collaboration and constructive critique, ultimately elevating the value and reach of their findings.