StatLab
Welcome to the StatLab
Yale University Library's StatLab supports all data, computational, and statistical inquiries. Whether you are an undergraduate researcher learning statistics for the first time, or a seasoned researcher looking for new tools to analyze complex data, we aim to provide quality support through 1-1 consultations, specialized workshops and instruction, and expertly crafted research guides.
1-1 Consultations
Step-by-Step Guide
How to Schedule a Consultation
1. Find a Consultant
Browse our team of consultants to find the best match for your research needs. Our consultants are trained to support a wide range of statistical and data-intensive research topics, from initial research design to interpreting complex outputs. We encourage you to review each team member's research interests and experience to ensure you get the most relevant support.
2. Book an Appointment with a StatLab Consultant
Select whether you would like to attend an in-person or virtual session and book your appointment:
- In-person consultations: Schedule an in-person appointment
- Virtual consultations: Schedule a virtual appointment
Select a time, and fill out the form with as much information as possible. If your consultation would benefit from sharing supporting materials (e.g. scripts, results, example articles, etc.) please send any to statlab@yale.edu.
Pro tip: The more detail you provide about your project beforehand, the more productive your consultation will be. Our consultants have limited time depending on demand, so thorough preparation helps us spend less time getting up to speed and more time providing high-quality guidance.
3. Meet With Your Consultant
Enjoy your personalized consultation session!
4. Share Your Feedback
Help us improve by completing our brief feedback survey after your consultation. Your input is essential for the continuous improvement of StatLab services.
Workshops & Instruction
StatLab Workshops
Upcoming Events
Introduction to R For Applied Statistics and Data Science
This workshop is designed to familiarize new and beginner users with the statistical programming language R. Participants will learn to work with common data structures, manage working directories, install and leverage external packages, and draw inferences from real-world data.
Schedule:
Optional Tech Clinic (software installation & setup): 8:45 – 10:15 a.m.
Core Workshop: 10:30 a.m. – 12:30 p.m.
Preparation: Bring a laptop with R and RStudio pre-installed if possible. Tech clinic available for setup assistance.
Introduction to Python for Data Science and Applied Statistics
This workshop introduces the essential tools for statistical and quantitative analysis in Python. Participants will learn to work with fundamental data structures, manage project directories, install and use key data-science libraries, create virtual environments, and draw inferences from real-world data.
Schedule:
Optional Tech Clinic (software installation & setup): 8:45 – 10:15 a.m.
Core Workshop: 10:30 a.m. – 12:30 p.m.
Preparation: Bring a laptop with Python 3 and Positron (or another IDE) installed. Tech clinic available for setup assistance.
Past Events
Introduction to R for Applied Statistics and Data Science
This workshop familiarizes participants with the R language. With a focus on good programming habits, learn to work with different data types, manage your workspace, use external packages, and make inferences from real-world data.
Introduction to Python for Applied Statistics and Data Analysis
Learn the basics of analyzing data with Python. This workshop focuses on data types, working directories, using external frameworks, managing dependencies with virtual environments, and making data-driven inferences.
From Scripts to Systems: Tips for Writing Professional and Reproducible Code
This workshop covers essential practices for professional coding, including project organization, naming conventions, and creating control files. Learn to write clear code with comprehensive documentation and proactive debugging.
Cleaning and Analyzing Complex Data with R Tidyverse
An intermediate R workshop on the Tidyverse suite. Learn to clean and merge data with dplyr, visualize with ggplot2, and chain functions with purrr and pipes. Intended for those with basic familiarity with R syntax.
Introduction to Python for Data Science and Applied Statistics
This workshop is designed to familiarize participants with the basic frameworks for analyzing statistical and quantitative data with Python. Participants will learn to identify and work with different types of data, set their working directory, use external frameworks, manage dependencies, and make inferences about real world data.
Cleaning and Analyzing Complex Data with R Tidyverse
This intermediate R workshop introduces the Tidyverse suite. Participants will learn to clean, summarize, and merge data with dplyr, visualize distributions with ggplot2, and chain functions with pipes. The workshop also covers reshaping data with tidyr and performing group-wise operations efficiently.
Working with Hierarchical and Web-based Data
This intermediate workshop covers collecting, managing, and analyzing web-based data via APIs. Learn to execute API requests, handle JSON/XML formats in R, and develop robust workflows for cleaning and merging datasets from multiple web sources using tools like httr2, jsonlite, and the tidyverse.
Working with Big Data in R
Learn to analyze datasets that exceed memory limitations. This workshop covers efficient storage with Apache Arrow, ETL pipelines, partitioning strategies, and using DuckDB. Gain skills in out-of-core processing and scalable data workflows.
Prerequisites: Proficiency in R and tidy code recommended.
Note: Requires access to the L2 Political dataset. Please request access one week prior.
Want a custom workshop?
We can deliver a customized session of a workshop to your department, group, or research lab. We'll tailor our core content to focus on your specific learning goals. To get started, please email us at statlab@yale.edu. We request at least one month's notice for all custom sessions.
Your request should include:
- A summary of the desired topic(s).
- The approximate number of participants.
We are flexible and can modify our existing workshops to feature new data, showcase different tools, meet discipline-specific needs, or even present on new tools and resources, depending on availability. If you just want to discuss possibilities or learn more, please don't hesitate to send us an email!
Research Guides
Coming Soon!
Our Team
StatLab Consultants
Cole Brookson
PhD Candidate
Epidemiology of Microbial Diseases
Atalay Demiray, MD
PhD Student
Health Policy & Management
Jonathan Elkobi
PhD Student
Political Science
Prabaha Gangopadhyay
PhD Candidate
Psychology
Jiye Kwon
PhD Candidate
Epidemiology of Microbial Diseases
Claudia Mastrogiacomo
PhD Candidate
Biostatistics
Workshop Calendar
The StatLab offers a range of workshops for beginners and topical workshops for users to get familiar with new-to-you functionality and features.
Statistical Support Workshop Materials
*iFrame not loading? You can also access the materials here: https://yale.box.com/s/0c4v1an8hlozxxj4j3dgdwg1k8znmh80