Qualitative Methods

Transparency in Experimental Political Science Research

April 9, 2024
Kamya Yadav
by Kamya Yadav. With the increase in studies with experiments in political science research, there are concerns about research transparency, particularly around reporting results from studies that contradict or do not find evidence for proposed theories (commonly called “null results”). To encourage publication of results with null results, political scientists have turned to pre-registering their experiments, be it online survey experiments or large-scale experiments conducted in the field. What does pre-registration look like and how can it help during data analysis and publication?

Elijah Mercer

Consultant
School of Information

Elijah Mercer is a Master's student in the School of Information. He is particularly interested in using data to drive results for marginalized communities. His interests are in the field of criminal justice, policy and juvenile justice.

Hilary Faxon, Ph.D.

Data Science Fellow
Environmental Science, Policy, and Management
Dr. Faxon is an ethnographer who uses social media and critical remote sensing to understand and reimagine social justice in technology, environment, and development in the Global South. She is an Assistant Professor of Environmental Social Science at the University of Montana.

Introduction to Propensity Score Matching with MatchIt

April 1, 2024
Alex Ramiller
by Alex Ramiller. When working with observational (i.e. non-experimental) data, it is often challenging to establish the existence of causal relationships between interventions and outcomes. Propensity Score Matching (PSM) provides a powerful tool for causal inference with observational data, enabling the creation of comparable groups that allow us to directly measure the impact of an intervention. This blog post introduces MatchIt – a software package that provides all of the necessary tools for conducting Propensity Score Matching in R – and provides step-by-step instructions on how to conduct and evaluate matches.

Computational Social Science in a Social World: Challenges and Opportunities

March 26, 2024
José Aveldanes
by José Aveldanes. The rise of AI, Machine Learning, and Data Science are harbingers of the need for a significant shift in social science research. Computational Social Science enables us to go beyond traditional methods such as Ordinary Least Squares, which face challenges in addressing complexities of social phenomena, particularly in modeling nonlinear relationships and managing high-dimensionality data. This paradigmatic shift requires that we embrace these new tools to understand social life and necessitates understanding methodological and ethical challenges, including bias and representation. The integration of these technologies into social science research calls for a collaborative approach among social scientists, technologists, and policymakers to navigate the associated risk and possibilities of these new tools.

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.

GPT Fundamentals

April 17, 2024, 3:00pm
This workshop offers a general introduction to the GPT (Generative Pretrained Transformers) model. We will explore how they reflect and shape our cultural narratives and social interactions, and which drawbacks and constraints they have.

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.

Nimita Gaggar

Consulting Drop-In Hours: By appointment only

Consulting Areas: Python, R, Qualitative methods, R Programming, Other, RStudio

Quick-tip: the fastest way to speak to a consultant is to first submit a request and then ...

Jane Angar

Consulting Drop-In Hours: Wed 9am-11am

Consulting Areas: R, Stata, LaTeX, Data Manipulation and Cleaning, Data Visualization, Qualitative methods, R Programming, Regression Analysis, Means Tests, Excel, Git or Github, Qualtrics, RStudio, Stata, Jupiter Notebook

Quick-tip: the fastest way to speak to a consultant is to first ...