Statistical Horizons

Learn how interpretable #machinelearning can reveal hidden structure in data, improve predictive performance, & add transparency in @CynthiaRudin's Distinguished Speaker seminar, “Interpretable Machine Learning: Visualization, Sparse Models, & Neural Networks,” June 17. statisticalhorizons.com/seminars/inter…

Join @gvazquezbare on June 23-26 for a course on the latest developments in #DifferenceinDifferences. You will learn to apply classical and novel methods for estimating treatment effects and to evaluate the assumptions behind them. statisticalhorizons.com/seminars/diffe…

Build reliable #AI-assisted data analysis workflows in “AI Tools for Data Analysis: From Chatbots to Coworkers” w/ @botzata, June 15-16. Learn to clean data, run analyses, create visualizations, and evaluate outputs using today’s AI tools. aihorizons.io/Seminars/ai-to…

In his blog post, “How AI Can Help You Build Better Experiments,” Charles Crabtree explains why LLMs are becoming important tools for experimental research—and why validation, documentation, and human review still matter. aihorizons.io/ai-build-bette…

Are you a researcher burdened by costly and time-consuming data collection? Join @lakens for "Sample Size Justification" on June 9-12 to learn how to justify your sample size, make the most of your resources, and efficiently test your hypothesis. statisticalhorizons.com/seminars/sampl…

Join the Machine Collaborators conversation Thurs., May 14, 7pm ET (11pm UTC) as @LexiPalmer_ presents “Silicon Sampling Under Different Sources of Uncertainty." Learn more: machinecollaborators.org

Join Adam D. Rennhoff for "Interpretable Machine Learning," June 9-12. Grounded in familiar statistical ideas, you'll learn tools and workflows to interpret, explain, and communicate complex #MachineLearning models, with hands-on demos in #Rstats. statisticalhorizons.com/seminars/inter…

Join @GolinoHudson for "LLM Text Generation in R: Practical Prompt Engineering" on June 3-4. In 8 hours (over 2 days), you'll learn to integrate #LLM models with #Rstats, engineer effective prompts, and apply LLMs to real research tasks and data analysis. aihorizons.io/Seminars/llm-t…

Learn how to design conjoint experiments, program surveys, analyze results, and communicate findings clearly in "Mastering Conjoint Analysis" with Andrew Heiss, June 2-5. statisticalhorizons.com/seminars/maste…

Join "Causal Mediation Analysis" with @valeritweety on June 2-5. Learn how to implement and interpret state-of-the-art #causalinference techniques, validate standard approaches, and apply regression methods for mediation with various outcomes. statisticalhorizons.com/seminars/causa…

Interested in getting started with #SEM? Join Paul Allison for "Structural Equation Modeling: Part 1" beginning June 1 for a 4-week self-paced introduction to this complex and wide-ranging methodology. No previous experience required. Part 2 coming in July! statisticalhorizons.com/seminars/struc…

In his new blog post, @brucedesmarais explains how the "black box problem" can affect generative #AI workflows through hidden errors, weak validation, and reproducibility challenges. aihorizons.io/black-box-prob…

Leverage the power of statistical models to deliver clear & compelling insights w/ confidence in "Interpreting & Communicating Statistical Results w/ #Rstats" w/ @VincentAB on May 28-29. Learn to illustrate your findings & create reproducible reports to convey results. statisticalhorizons.com/seminars/inter…

Gain a thorough intro to #causalinference in randomized field trials in "Experimental Methods" w/ Henry May on May 18-20. We'll cover key aspects of designing & conducting experiments that meet the requirements of many grant programs focused on intervention research. statisticalhorizons.com/seminars/exper…

Join Distinguished Speaker @CynthiaRudin, June 17, for “Interpretable Machine Learning: Visualization, Sparse Models, & Neural Networks.” Learn how interpretable #machinelearning can visualize complex data, build sparse models for tabular data, & clarify computer vision predictions. statisticalhorizons.com/seminars/inter…

Join us for Machine Collaborators, a free conversation series on how researchers are using #AI. On Thurs., April 30 at 7pm ET (11pm UTC), @mitchellbosley presents “Principles of Agentic Research,” where he’ll discuss working with AI agents. Learn more: machinecollaborators.org

Join @brucedesmarais for "Advanced Machine Learning & Applied AI Workflows", May 13-15. Go beyond prediction—address causal inference, missing data, LLMs, and more while building stronger #AI workflows with advanced #machinelearning methods in #Rstats. aihorizons.io/Seminars/advan…

Want a smoother coding and collaboration workflow? Join @AaronGullickson for the 1-day seminar “Using Version Control for Data Analysis through GitHub” on April 22. Learn the basics of #git, collaboration, and common troubleshooting steps. statisticalhorizons.com/seminars/versi…

Looking for more sophisticated methods to handle your complex designs and modeling objectives? Learn cutting edge "Multilevel Structural Equation Modeling" (MSEM) and other multilevel modeling extensions w/ @KristopherJPre1 on May 13-15 & 18-20. statisticalhorizons.com/seminars/multi…

We’re excited to co-sponsor Machine Collaborators, a free conversation series led by Charles Crabtree on how researchers are using #AI in their work. Join the 1st session Thur, April 16 at 7pm ET (11pm UTC), as @brhkim discusses accelerating quantitative research w/ AI agents. Learn more: machinecollaborators.org