Statistical Horizons offers expert-led online training in statistics and research methods; AI Horizons extends that mission into practical AI for researchers.
Joined December 2014
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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.
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Join @brucedesmarais for "Machine Learning" July 21-24 to learn how #machinelearning can be used to uncover valuable insights, identify optimal model structures, perform variable selection, and deliver highly accurate predictions from data.
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Transform how you design and analyze experiments in “Using AI to Build Better Experiments” with Charles Crabtree, July 14-17. Discover how to use #LLMs to create materials, augment studies, and interpret results.
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Learn advanced structural equation modeling (#SEM) topics like instrumental variables, alternative estimation methods, multiple group models, & models for longitudinal data at your own pace. 4-week course "SEM: Part 2" On Demand with Paul Allison starts July 13.
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In the next free Machine Collaborators session, @LIANJie_Jason presents “Learning with AI,” on what it means for researchers to expand their knowledge boundaries while understanding the products, processes, and limits of AI-assisted workflows. Join June 11 at 7pm ET (11pm UTC).
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Working with binary or ordinal outcomes in #SEM? "Structural Equation Modeling with Categorical Data" with Sonja Winter, July 7-10, covers key approaches to model specification, estimation, and interpretation for categorical data, with examples in #Mplus and #Rstats.
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Looking to strengthen your research with #AI tools? Join @EthanBusby on July 7-10 for "Using #LLMs for Social Science Research"! Learn the fundamentals of large language models (like #ChatGPT) and how to integrate them into your research.
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Learn the basics of #Python in 4 days! Join Edwin Dalmaijer for "Introduction to Python for Data Analysis" on June 23-26 to explore how to use Python for data analysis, including handling datasets and writing full analyses. statisticalhorizons.com/semi…
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How can agentic #AI help researchers share their work beyond the academy? Join @akoustov on Thurs., May 28 at 7pm ET (11pm UTC) as he presents “Using Agentic AI to Improve Your Public Engagement as a Researcher” in the next Machine Collaborators session. Learn more: machinecollaborators.org/
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Join "Meta-Analysis" w/ David Wilson June 23-26 to learn to conduct all aspects of a meta-analysis. Gain the skills to search for studies to include, code & extract data, compute effect sizes, estimate models, explore publication selection bias, & report results using #Rstats, @Stata, or #SPSS. statisticalhorizons.com/semi…
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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/semi…
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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…
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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…
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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/semi…
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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/
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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/semi…
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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…
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Learn how to design conjoint experiments, program surveys, analyze results, and communicate findings clearly in "Mastering Conjoint Analysis" with Andrew Heiss, June 2-5.
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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/semi…
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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/semi…
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