RStudio

Chirag Manghani

Consulting Drop-In Hours: Wed 1pm-3pm

Consulting Areas: Python, R, SQL, Stata, SAS, LaTeX, HTML / CSS, Javascript, C++, APIs, Cloud & HPC Computing, Cybersecurity & Data Security, Databases & SQL, Data Manipulation and Cleaning, Data Science, Data Sources, Data Visualization, Deep Learning, Machine Learning, Natural Language Processing, Python Programming, R Programming, Software Tools, Text Analysis, Web Scraping, Regression Analysis, Software Output Interpretation, Bash or Command Line, Excel, Git or Github, Qualtrics, RStudio, RStudio...

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 ...

Nicolas Nunez-Sahr

Consulting Drop-In Hours: By appointment only

Consulting Areas: Python, R, SQL, C++, APIs, Databases & SQL, Data Manipulation and Cleaning, Data Science, Data Visualization, Deep Learning, Machine Learning, Natural Language Processing, Python Programming, R Programming, Text Analysis, Regression Analysis, Software Output Interpretation, Bash or Command Line, Git or Github, RStudio, Google Cloud, PostgreSQL, Python Django

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

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 ...

Lauren Chambers

Consulting Drop-In Hours: Wed 11am-1pm

Consulting Areas: Python, R, HTML / CSS, APIs, Data Manipulation and Cleaning, Data Science, Data Visualization, Python Programming, R Programming, Software Tools, Web Scraping, Regression Analysis, Software Output Interpretation, Bash or Command Line, Git or Github, OCR, RStudio

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

Reine Ngnonsse

IUSE Undergraduate Advisory Board
Genetics and Plant Biology

Reine Ngnonsse, an enthusiast for math and technology, delved into tutoring math at a community college through the EOPs program. At UC Berkeley, while pursuing Genetics and Plant Biology, She explored R programming in a CRISPR project. As an intern at Health Career Connection, Reine expanded coding skills in Python, R, and Tableau, igniting a passion for programming. With exposure to Python and Javascript, she can't wait to merge mathematical prowess with coding finesse for innovative solutions.

Addison Pickrell

IUSE Undergraduate Advisory Board
Mathematics
Sociology

Addison is an aspiring mathematician and social scientist (Class of '27). He loves collecting books he'll never read, is an open-source and open-access advocate, and an aspiring community organizer and systems disrupter. Ask me about community-based participatory action research (CBPAR), critical pedagogy, applied mathematics, and social science.

Mapping Census Data with tidycensus

November 6, 2023
Alex Ramiller
by Alex Ramiller. The U.S. Census Bureau provides a rich source of publicly available data for a wide variety of research applications. However, the traditional process of downloading these data from the census website is slow, cumbersome, and inefficient. The R package “tidycensus” provides researchers with a tool to overcome these challenges, enabling a streamlined process to quickly downloading numerous datasets directly from the census API (Application Programming Interface). This blog post provides a basic workflow for the use of the tidycensus package, from installing the package and identifying variables to efficiently downloading and mapping census data.

María Martín López

Data Science Fellow
Psychology

María Martín López is a PhD student in the Cognition area within the Department of Psychology. Her research relates to cognitive computational and quantitative models of individual differences in behaviors, thoughts, and emotions. She is particularly interested in how we can create and leverage novel algorithms to understand, measure, and predict processes relating to externalizing psychopathology (e.g. impulsivity, aggression, substance use). She answers these questions using a range of computational and quantitive models including AI, NLP, SEM, time series analysis, multi-level...

Using Forest Plots to Report Regression Estimates: A Useful Data Visualization Technique

October 17, 2023
Sharon Green
by Sharon Green. Regression models help us understand relationships between two or more variables. In many cases, results are summarized in tables that present coefficients, standard errors, and p-values. Reading these can be a slog. Figures such as forest plots can help us communicate results more effectively and may lead to a better understanding of the data. This blog post is a tutorial on two different approaches to creating high-quality and reproducible forest plots, one using ggplot2 and one using the forestplot package.