R

R Fundamentals: Parts 1-4

September 20, 2022, 1:00pm
This workshop is a four-part introductory series that will teach you R from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the open-sourced R Studio software, understand data and basic manipulations, import and subset data, explore and visualize data, and understand the basics of automation in the form of loops and functions. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research.

Frances Leung

Data Science Fellow
School of Information

Frances Leung is a master’s student at UC Berkeley School of Information where she focuses her studies in information and data science. She has a keen interest in leveraging data-driven insights to better understand consumer behaviors and the world around us. In her professional work as a management consultant, she advises retailers and consumer businesses on digital transformation and creating web/mobile experiences that delight consumers through a human-centered approach. Frances holds a Master in Business Administration from York University, Schulich School...

Irene Farah

Instructor
City and Regional Planning

Irene is a PhD student in City and Regional Planning. Her research interests lie at the intersection of urban geography, political science, and public health. In particular, she studies street vendors in Mexico City and how the spatiality and politics of their working conditions impact their access to healthy food. She strongly believes in connecting with other social scientists to share perspectives on how to use technology to acquire greater knowledge of social phenomena.

Sam Temlock

Data Science Fellow
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.

Connor Haley

Data Science Fellow
Haas School of Business

Connor is an MBA/MEng student with an undergraduate degree in statistics. He spent the past three years in economic consulting, focused on designing competitive electric power markets to produce optimal outcomes. His technical background is in R, Excel, Visual Basic (VBA/macros), and statistical methods.

R Fundamentals: Parts 1-4

August 15, 2022, 10:00am
This workshop is a four-part introductory series that will teach you R from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the open-sourced R Studio software, understand data and basic manipulations, import and subset data, explore and visualize data, and understand the basics of automation in the form of loops and functions. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research.

Christopher Paciorek, Ph.D.

Research Computing Consultant, Adjunct Professor
Department of Statistics
Research IT

Chris Paciorek is an adjunct professor in the Department of Statistics, as well as the Statistical Computing Consultant in the Department's Statistical Computing Facility (SCF) and in the Econometrics Laboratory (EML) of the Economics Department. He is also a user support consultant for Berkeley Research Computing. He teaches and presents workshops on statistical computing topics, with a focus on R.

Marina Blum

Data Science Fellow
School of Public Health

Marina is a master's student in the Health and Social Behavior division of the School of Public Health. She has extensive experience in ATLAS.ti and can help you get the most out of the program. She is passionate about data visualization, and is happy to help with related questions and questions on qualitative methods.

Diana Casanova

Consultant
Graduate School of Education

Diana Casanova is a fourth-year Ph.D. candidate with the Graduate School of Education. Diana’s research is focused on the policies and practices that empower family and community stakeholders to act collectively and affect social change. Specifically, she studies the implementation of California’s school finance reform, which includes a more structured and democratic process of stakeholder engagement, seeking to illustrate the relationship between a state initiative aimed at bringing families into policy-making spaces and the ways that families find and make meaning in these spaces...

Maya Samuels-Fair

Instructor, Consultant
Integrative Biology

Maya is an Integrative Biology Ph.D. student in the Finnegan Marine Paleobiology Lab, where she studies life-history evolution and diversity patterns in the marine invertebrate fossil record. She is happy to help with statistical analyses, data visualizations, and simulations in R. She also has recently been dabbling in image analysis, including python-based machine learning and 3D Slicer extension development, and would love to help other newcomers get started.