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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 4-Day Livestream Seminar Taught by Charles Crabtree, Ph.D.

Getting More Done Without Losing Control

Many researchers already use AI in small, informal ways—summarizing papers, cleaning text, drafting code, or checking results. What’s often missing is a clear, practical framework for using AI systematically while keeping accuracy, judgment, and responsibility firmly in human hands.

AI agents can dramatically speed up research processes, but they can also make mistakes harder to detect. This seminar shows you how to move routine work to AI while slowing down at exactly the points where human judgment is essential. The goal is not “automated research,” but more careful research conducted more efficiently.

This 4-day introductory seminar focuses on AI agent-driven research workflows: simple, structured ways to use multiple AI tools together to reduce low-value work while avoiding hidden errors. You’ll learn how to break projects into steps, design multi-stage workflows with built-in checks, and document AI use clearly so that your process remains transparent and reviewable. Examples draw from quantitative, qualitative, and mixed-methods research, with an emphasis on principles that transfer across disciplines. No prior experience with AI agents is assumed.

By the end of the course, you will have the skills to:

• • Identify which research tasks are safe to speed up—and which are not.
  • Use AI to reduce low-value work without delegating judgment.
  • Build simple multi-step workflows that include built-in checks.
  • Recognize common AI errors before they affect results.
  • Decide where human review is essential and where it is optional.
  • Clearly explain and document how AI was used in a project.