R

R Geospatial Fundamentals: Parts 1-3

October 14, 2024, 2:00pm
Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The R programming language is a great platform for exploring these data and integrating them into your research. This workshop focuses on fundamental operations for reading, writing, manipulating and mapping vector data, which encodes location as points, lines and polygons.

R Machine Learning with tidymodels: Parts 1-2

October 14, 2024, 1:00pm
Machine learning often evokes images of Skynet, self-driving cars, and computerized homes. However, these ideas are less science fiction as they are tangible phenomena that are predicated on description, classification, prediction, and pattern recognition in data. During this two part workshop, we will discuss basic features of supervised machine learning algorithms including k-nearest neighbor, linear regression, decision tree, random forest, boosting, and ensembling using the tidymodels framework. To social scientists, such methods might be critical for investigating evolutionary relationships, global health patterns, voter turnout in local elections, or individual psychological diagnoses.

R Fundamentals: Parts 1-4

October 8, 2024, 5:00pm
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.

R Fundamentals: Parts 1-4

September 17, 2024, 9:00am
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.

R Data Wrangling and Manipulation: Parts 1-2

October 1, 2024, 1:00pm
It is said that 80% of data analysis is spent on the process of cleaning and preparing the data for exploration, visualization, and analysis. This R workshop will introduce the dplyr and tidyr packages to make data wrangling and manipulation easier. Participants will learn how to use these packages to subset and reshape data sets, do calculations across groups of data, clean data, and other useful tasks.

Sakina Dhorajiwala

Availability: By appointment only

Consulting Areas: Python, R, Stata, LaTeX, Data Manipulation and Cleaning, Data Visualization, Mixed Methods, Qualitative Methods, Surveys, Sampling & Interviews, Regression Analysis, Excel, Git or Github, RStudio

Pratik Sachdeva, Ph.D.

Availability: By appointment only

Consulting Areas: Python, R, SQL, Databases & SQL, Data Manipulation and Cleaning, Data Science, Data Sources, Data Visualization, Deep Learning, Machine Learning, Python Programming, R Programming, Regression Analysis, Hierarchical Models, Means Tests, Software Output Interpretation, Bash or Command Line, Excel, Git or Github, RStudio

Tom van Nuenen, Ph.D.

Availability: By appointment only

Consulting Areas: Python, R, SQL, LaTeX, HTML / CSS, Javascript, Julia,Data Manipulation and Cleaning, Data Science, Data Visualization, Digital Humanities, Machine Learning, Mixed Methods, Natural Language Processing, Python Programming, Qualitative methods, R Programming, Surveys, Sampling & Interviews, Text Analysis, Web Scraping,Regression Analysis,Bash or Command Line, Excel, Gephi, Git or Github, NVivo, Qualtrics, RStudioFairness, Perceptions of AI, Hermeneutics

Yue Lin

Data Science Fellow 2024-2025
Political Science

Yue is a Ph.D. student in Political Science at the University of California, Berkeley, with a Designated Emphasis on Political Economy. Using mixed methods, she studies foreign lobbying, geopolitical risk, and economic security to understand when, how, and why multinational corporations become the targets and weapons of state power rivalry.

Paul Salamanca

Instructor
Sociology

I am a PhD student in sociology. I study imperialism, race, and gender, with a historical focus on the colonial Philippines. In my free time, I like to cook and bake.