Using LLMs for Social Science Research – February 2027

Event Phone: 1-610-715-0115

Details Price Qty
Regular Admissionshow details + $995.00 USD  ea 

Upcoming Dates

  • 10
    Feb
    Using LLMs for Social Science Research
    10:00 AM
    -
    3:30 PM
Cancellation Policy: If you cancel your registration two weeks or more before the course is scheduled to begin, you are entitled to receive your choice of either a credit for a future seminar (which can be applied toward any of our courses) or a refund of the registration fee (minus a processing fee of $50). 
In the unlikely event that Statistical Horizons LLC must cancel a seminar, we will do our best to inform you as soon as possible of the cancellation. You would then have the option of receiving a full refund of the seminar fee or a credit towards another seminar. In no event shall Statistical Horizons LLC be liable for any incidental or consequential damages that you may incur because of the cancellation.
A 3-Day Livestream Seminar Taught by Ethan C. Busby, Ph.D.

This seminar explores how to integrate large language models (LLMs) into research on human attitudes and behavior. It provides an introduction to LLMs like ChatGPT, Claude, Gemini, DeepSeek, and Llama, discusses the critical concept of prompt engineering, and teaches you how to use LLMs in three common use cases:

  1. Coding open-ended survey responses
  2. Generating simulated or synthetic samples
  3. Using LLMs as treatments in randomized experiments

The course is designed to give you the tools you need to start using LLMs in your own work. You’ll gain a foundational understanding of generative AI tools, the most efficient ways to interact with them, and detailed knowledge of how to apply LLMs in the three common use cases listed above.

This seminar includes a set of exercises and supplemental tutorials to help you apply the skills you learn on your own. By working through these applications, you will gain the ability to effectively use LLMs in your own projects.

As a foundation for the course, you will first receive an accessible introduction to the history, structure, and nature of large language models (LLMs). We will then turn to the differences between LLMs of different types (open- and closed-source LLMs, LLMs provided by different companies, etc.).

A significant amount of seminar time will be devoted to “prompt engineering” or principles of interacting with LLMs. We will contrast this with fine-tuning (which we will only discuss at a conceptual level) and cover different approaches and methods to prompting. You will spend time exploring methods of prompting with LLMs.

The course will provide detailed demonstrations of how to interact with LLMs in public-facing interfaces (like ChatGPT), online developer platforms, and through APIs in R and RStudio. You will be given time to work through exercises and gain experience working with these interfaces as a part of the seminar.

The final part of the course covers three common use cases: coding open-ended survey responses, generating simulated or synthetic samples, and using LLMs as treatments in randomized experiments. Of these three, we will devote more time to synthetic samples and treatments than to coding open-ended texts.

Venue: