Tutorial Overview
Focus: Using AI to support exploratory and early-stage analysis.
This session would introduce ways AI can assist with foundational analysis tasks, such as summarizing data, identifying patterns, suggesting appropriate baseline methods, and helping interpret descriptive outputs. The goal is not to replace statistical judgment, but to help participants move more efficiently through the first pass of analysis.
Possible hands-on activities:
- Generate descriptive summaries of a small dataset
- Ask AI to suggest appropriate baseline analyses for different data types
- Draft code for summary statistics, simple visualizations, or basic models
- Compare multiple candidate approaches for an initial analysis
- Interpret example outputs and discuss what they do, and do not, mean
About the Series
This tutorial series introduces practical ways researchers can use AI to support common stages of the research workflow. Designed as a hands-on learning experience, the series focuses on approachable, real-world applications rather than abstract theory. Each session will combine brief framing, live demonstrations, and guided practice so participants can explore how AI tools may help with tasks such as refining research questions, working with data, conducting early-stage analysis, checking outputs, and communicating findings responsibly. The goal is to help researchers develop useful habits for integrating AI into their work in thoughtful, transparent, and effective ways.