See how @kjhealy.co builds trustworthy visualizations at #positconf2025 —then level up your own skills in his course on "Data Wrangling with the #Tidyverse", Jan. 7–9.

Join “Latent Growth Curve Modeling,” Dec. 10-12 with @dmcneish.bsky.social. Learn how to model change over time, understand growth factors, and apply growth models in your research.

Struggling with missing data? Join Paul Allison for "Missing Data Using R", a 4-week on-demand seminar starting Nov. 17. You'll learn maximum likelihood & multiple imputation—two of the most powerful #missingdata solutions using #Rstats.

Join Roy Levy on Dec. 10-12 for "Applied Bayesian Data Analysis: A Second Course" to take your #Bayesian skills to the next level! Master key skills in advanced modeling frameworks, including factor analysis, structural equation models, and multilevel models.

Check out the Data Science at Home podcast for insights on AI, machine learning, and tech innovation. Listen to the latest episode here.

Learn to model change or growth in #longitudinal data using "Latent Growth Curve Modeling" with @dmcneish.bsky.social, December 10-12. You'll walk away with the ability to confidently apply and interpret these methods to answer your unique research questions.

Distinguished Speaker Kosuke Imai presents "Evaluating AI & Machine Learning Algorithms for #causalinference", Feb. 10. Learn to assess #AI & #machinelearning practically—from heterogeneous treatment effects, individualized treatment rules, & human–AI collaboration.

Distinguished Speaker Kosuke Imai presents "Evaluating AI & Machine Learning Algorithms for #causalinference", Feb. 10. Learn to assess #AI & #machinelearning practically—from heterogeneous treatment effects, individualized treatment rules, & human–AI collaboration.

Join Simon Brewer on December 4-6 for "Spatial Analysis of Health Data"! Explore how geospatial #healthdata provide the tools to better understand & tackle public health challenges while addressing the issues that can arise while working with this type of data.

Forecasting requires tools built for time series. ARIMA (AutoRegressive Integrated Moving Average) models capture trends & seasonality where regression fails. Read more on the SH blog, then join Fundamentals of Time Series Analysis w/ Daniel J. Henderson, Nov. 12-14.

Want to improve or expand how you analyze #qualitative research—integrating computational tools & AI? Join Corey M. Abramson Dec. 3–5 for "Computer-Assisted Qualitative Data Analysis with Automation & AI". Ideal for those new to QDA software or coding.

Join "Mediation and Moderation Analysis for Simple Within-Subject Designs" with @akmontoya.bsky.social, Nov. 20-21. Using the MEMORE macro, created by the instructor, learn cutting-edge methods for estimating and interpreting effects in within-subject designs in 8 hours (over 2 days).

Join "Missing Data Using R" with Paul Allison starting Nov. 17. This 4-week on-demand seminar covers the theory and practice of maximum likelihood and multiple imputation, two of the latest and most accurate methods to handle #missingdata, all using #Rstats.

Join Daniel J. Henderson for "Fundamentals of Time Series Analysis" on November 12-14 for an introduction to time series methods for univariate and multivariate models. Learn how to program and apply these methods in practice using #Rstats and how to present results.

Join "Psychometrics" w/ @mattadiemer.bsky.social on Nov. 12-14 to learn about #psychometrics and how to to understand, detect, and remediate bias in measures. Topics include exploratory factor analyses, confirmatory factor analyses, MIMIC models, invariance & more.

What is the epigenome, and why does it matter? Find out in Jennifer Smith’s "Introduction to Epigenomics," Nov. 5-7. You'll learn to manage, clean, & model #epigenomic data, understand DNA methylation, and create & use biomarkers to enhance your health & environmental research.

Join "Latent Transition Analysis" on Oct. 31-Nov. 1 w/ Bethany Bray and Stephanie Lanza. Extend your latent class and latent profile analyses (LCA & LPA) skills to longitudinal data with LTA and learn how to examine how subgroup memberships change over time.

Distinguished Speaker, Benjamin Bolker (@bbolker.bsky.social), presents “Mixed Models in the Wild: Techniques, Workflows, and Challenges,” Nov. 18. He’ll cover core concepts, walk through modeling workflows, and address common challenges like sparse data and model complexity.

Earn your Measurement and Psychometrics Certification! Gain the skills and recognition that showcase your ability to design, test, and validate measures with confidence. Contact us to learn more.

Expand your #Python skillset w/ Adam Rennhoff’s "Python for #Rstats Users", Oct. 29-30. Discover how to leverage Python’s strengths within your familiar RStudio environment & take advantage of Python’s superior abilities to work with 'big data' and fit models.

Join Boris Nikolaev on Oct 22-23 for "Data Analysis with ChatGPT: A Practical Introduction"! Explore the strengths and limitations of ChatGPT as a data analysis tool in real-world scenarios to work with complex data and create compelling visualizations.

Learn to create and publish a professional, data-focused website in “Create an Online Presence with Quarto Websites” on October 16-17, with @andrew.heiss.phd‬! Discover how to use #Quarto to build a variety of websites like personal portfolios, research compendiums, and interactive dashboards.

From disease surveillance to healthcare access, spatial analysis transforms health research. See how in Simon Brewer’s "Spatial Analysis of Health Data" seminar, Dec. 4-6--learn mapping, regression, & spatiotemporal methods. View the 1st hour now: youtu.be/7vUiqoCiqsE

Discover how to apply mediation & moderation analysis in within-subject designs. Join @akmontoya.bsky.social's seminar Nov. 20-21 to learn to interpret & estimate total, direct, indirect, and conditional effects using the MEMORE macro, developed by the instructor. Watch the first hour now.

Are you interested in learning how to implement structural equation modeling (SEM) methods in your research? Join "Structural Equation Modeling Done Right" w/ Rex B. Kline, Oct. 15-17 to distinguish your own work in #SEM by following best practices and avoiding common mistakes.

Looking to estimate #causal effects from observational data? (You probably are!) Join @stephenvaisey.com for "Treatment Effects Analysis" starting Oct. 13. This 4-week on-demand seminar covers methods like propensity-score matching, inverse probability weighting, and entropy balancing.

Learn how to create and validate psychometric scales using #AI and #Rstats. Join @hudsongolino.bsky.social for "Automatic Item Generation and Validation," Sept. 10–11. The first hour, now on YouTube, introduces the motivation and key concepts behind the method.

Join "Propensity Score Analysis: Advanced" w/ Shenyang Guo, Oct. 9-11, to strengthen your PSA skillset. Learn advanced PSA topics like Heckman's kernel-based matching, Hirano & Imbens's generalized model for dosage analysis, subclassification, & Rosenbaum sensitivity analysis.

Get certified in #AI! Learn ChatGPT, text generation & classification, prompt engineering, & more through 4 expert-led seminars—and gain an "AI-Enabled Data Analytics" credential that showcases your expertise & strengthens your CV. Contact for more info: bit.ly/ai-bsky-sh

Join "Multilevel and Mixed Models Using R" with @stephenvaisey.com on Oct. 8-10 for an intensive intro to multilevel models. Learn the (real) difference between fixed & random effects and how to combine the strengths of both into a single model using #Rstats.

Join "Introduction to Text as Data" with Amber Boydstun & @corystruthers.bsky.social on Oct. 1-3 to learn text-as-data methods, including how they work, how they can be applied, and common pitfalls to avoid by drawing on social science research and perspectives.

Learn #Rstats in 3 days with Andrew Miles! Join "Introduction to R for Data Analysis" on October 1-3 for hands-on experience using & tailoring R to your own research, with topics like R functions and coding in R, descriptive stats, bivariate plots, and linear models.

Is your team making decisions based on biased data? Propensity Score Analysis helps you compare “apples to apples” and find the true impact. Read the Statistical Horizons blog to see how—and join our Sept. 18-20 seminar to master these methods. bit.ly/psablog-sh

Watch the first hour of "Introduction to Epigenomics" with Jennifer Smith—now on YouTube. Join the full seminar Nov. 5–7 to learn how to analyze DNA methylation data, run epigenome-wide association studies (EWAS), and build #epigenetic biomarkers.

Looking to strengthen your research with AI tools? Join @ethanbusby.bsky.social on Sept. 25-27 for "Using Large-Language Models for Social Science Research"! Learn the fundamentals of large language models (like ChatGPT) and how to integrate them into your research.

Learn to analyze event-time data in "Survival Analysis", taught on-demand by Dr. Paul Allison starting Sept. 22. This 4-week self-paced course will cover topics like censoring, Kaplan-Meier estimation, Cox regression, discrete-time methods, competing risks, and repeated events.

Learn to estimate treatment effects w/ nonexperimental or observational data in "Propensity Score Analysis: Basics" w/ Shenyang Guo, Sept. 18-20. Covering estimating #propensityscores, classic & optimal matching, propensity score weighting, Abadie & Imbens’ matching estimators.

Join "Automatic Item Generation and Validation: A Network Integrated Approach using Large Language Models in R" on Sept. 10-11 with @hudsongolino.bsky.social to learn how to use artificial intelligence to create and validate questionnaires and scales!

Already have a background in social network analysis & looking to expand your knowledge? Join John Skvoretz for "Social Networks: Statistical Approaches" starting Sept. 8 to learn statistical methods for analyzing social network data using #Rstats in this 4-week on-demand course.

Learn #Bayesian methods with @roylevy.bsky.social in "Applied Bayesian Data Analysis", Sept. 4-6! Topics include model construction, graphical representation of models, model comparisons, Markov chain Monte Carlo (MCMC) estimation, & more.

Join "Bluesky Data: Collection, Cleaning, and Analysis" with @resulumit.bsky.social on Aug. 26-27! Learn to access the #Bluesky API, clean social media data, and apply text & network analysis using #Rstats in this hands-on course.

Discover how #Bayesian methods for #qualitativeresearch can help you formulate clear hypotheses, avoid biases, and draw well-supported conclusions using practical applications & case studies. Join "Bayesian Analysis for Qualitative Evidence" on Aug. 26-27, taught by Tasha Fairfield.

Join Dr. Gonzalo Vazquez-Bare on Aug. 19-22 for a course on the latest developments in #Difference-in-Differences. You will learn to apply classical and novel methods for estimating treatment effects and to evaluate the assumptions behind them.

Welcome our next Distinguished Speaker, John P. A. Ioannidis, for “Reproducible and Useful Research: The Replication Crisis and Solutions”, Aug. 11. Explore the causes of irreproducibility & learn practical, evidence-based ways to improve reliability.

Learn how to extend latent class analysis (LCA) to longitudinal data w/ "Latent Transition Analysis," Oct. 31-Nov. 1. Bethany Bray & Stephanie Lanza cover model selection, measurement invariance, predictions, & more. Watch the 1st hour now!

Explore Monte Carlo simulations, a valuable tool for understanding, evaluating, comparing, & applying a wide array of statistical methodologies. Join Ashley Naimi Aug. 19-22 for "Design & Analysis of Simulation Studies" to learn to implement your own simulation using #Rstats.

Looking to strengthen your #causalinference skills? Join @noahgreifer.bsky.social on Aug. 12-15 for "Causal Inference in R Using MatchIt and WeightIt" to gain the skills to apply these #Rstats packages to estimate and interpret treatment effects.

Join @dmcneish.bsky.social for "Dynamic #StructuralEquationModeling", Aug 12-15! Explore DSEM, a cutting-edge framework that utilizes intensive longitudinal data to gain detailed insights into dynamic processes and variability within and between subjects.

Curious how Python can expand your R workflow? Watch the first hour of "Python for #Rstats Users" with Adam D. Rennhoff, then join the Oct. 29–30 seminar to build hands-on #Python skills for data science, #machinelearning, and #deeplearning.

Learn to use natural language processing (NLP) techniques & large language transformer models - #LLMs - for research applications. Join "Text Classification with Large Language Transformer Models in #Rstats" w/ @hudsongolino.bsky.social on Aug. 5-8.