Means Tests

Sharazad Ali

Consulting Drop-In Hours: By appointment only

Consulting Areas: Cluster Analysis, Databases and SQL, Data Visualization, Diversity in Data, Excel, Experimental Design, Focus Groups and Interviews, Machine Learning, Means Tests, Python, Qualitative Methods, Qualtrics, R, Regression Analysis, RStudio Cloud, Software Output Interpretation, SQL, Time Series

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

Lance Santana

Consulting Drop-In Hours: By appointment only

Consulting Areas: APIs, ArcGIS Desktop - Online or Pro, Bayesian Methods, Cluster Analysis, Data Visualization, Databases and SQL, Excel, Git or GitHub, Java, Machine Learning, Means Tests, Natural Language Processing (NLP), Python, Qualtrics, R, Regression Analysis, Research Planning, RStudio, Software Output Interpretation, SQL, Survey Design, Survey Sampling, Tableau, Text Analysis

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

Aidan Lee

Consulting Drop-In Hours: By appointment only

Consulting Areas: ArcGIS Desktop - Online or Pro, Bayesian Methods, Causal Inference, Cluster Analysis, Data Sources, Data Visualization, Databases and SQL, Digital Health, Excel, Experimental Design, Geospatial Data: Maps and Spatial Analysis, Git or GitHub, LaTeX, Machine Learning, Means Tests, Mixed Methods, Natural Language Processing (NLP), OCR, Python, Qualtrics, R, Regression Analysis, Research Design, Research Planning, RStudio, RStudio Cloud, SAS, Software Output Interpretation, SPSS, SQL,...

Sohail Khan

Senior Data Science Fellow 2025-2026, Data Science Fellow 2024-2025
School of Information

Hey everyone, I’m Sohail - a 1st years Master’s student studying Data Science at the I-School. I am interested in the intersection between Computer Science, Data Science, and Cognitive Psychology and using these tools to understand, discover, and drive the development of assistive technologies.

I have experience building with brain computer Interfaces, developing distributed data processing applications, and am currently working on a large scale archival project aimed at preserving the history and memory of resistance movements through an embedding based...

Jane (Mango) Angar

Senior Data Science Fellow 2025-2026, Data Science Fellow 2024-2025
Political Science

Hi! I am a PhD candidate in the Political Science Department at UC Berkeley. My dissertation traces the emergence of disability rights groups in Africa, focusing on Zambia and Malawi, and examines factors influencing their effectiveness. I use mixed methods, including archival work, field interviews, participant observation, and surveys for data collection.

My data analysis techniques include text analysis, social network analysis, means tests, and regressions. In my free time, I enjoy moderately difficult hikes, walks along the beach with my dog, Princess, and...

Carly Karrick

Data Science & AI Fellow 2025-2026
Department of Environmental Science, Policy, and Management

Carly is a Ph.D. candidate in the Environmental Science, Policy, and Management Department. As an environmental microbiologist, Carly is excited by questions about how microorganisms influence host health. Specifically, Carly studies how microalgae, bacteria, and viruses influence coral disease in the Caribbean and Gulf of Mexico, and how these microorganisms are distributed on Pacific coral reefs. Her research utilizes a range of data science and bioinformatic tools to integrate DNA- and RNA-based signatures of microbial activity with microscopy image analysis. Carly received...

Sarah Daniel

Data Science & AI Fellow 2025-2026
Political Science

Sarah Daniel is a PhD candidate in Political Science, specializing in urban politics in Sub-Saharan Africa, with a particular focus on East Africa. Her research examines how neighborhood communities organize for collective action to improve service delivery, reduce inequality, and enhance political representation.

Skyler Yumeng Chen

Data Science & AI Fellow 2025-2026, 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.

Predicting the Future: Harnessing the Power of Probabilistic Judgements Through Forecasting Tournaments

April 29, 2025
Christian Caballero
by Christian Caballero. From the threat of nuclear war to rogue superintelligent AI to future pandemics and climate catastrophes, the world faces risks that are both urgent and deeply uncertain. These risks are where traditional data-driven models fall short—there’s often no historical precedent, no baseline data, and no clear way to simulate a future world. In cases like this, how can we anticipate the future? Forecasting tournaments offer one answer, harnessing the wisdom of crowds to generate probabilistic estimates of uncertain future events. By incentivizing accuracy through structured competition and deliberation, these tournaments have produced aggregate predictions of future events that outperform well-calibrated statistical models and teams of experts. As they continue to develop and expand into more domains, they also raise urgent questions about bias, access, and whose knowledge gets to shape our collective sensemaking of the future.

Sam Temlock

Data Science Fellow 2021-2022
School of Information

Sam (he/him) is a Master of Information and Data Science graduate student at the School of Information, with experience in Cybersecurity and Network Programming. He holds a BS in Computer Systems Engineering from Rensselaer Polytechnic Institute and has previous experience in consulting at Deloitte. He has experience with Python, R, SQL, machine learning, data analytics, statistical analysis, and research design.