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Announcing Statistical Horizons’ Spring 2022 Seminars


Announcing Statistical Horizons’ Spring 2022 Seminars

Statistical Horizons offers short seminars on a wide variety of advanced statistical topics. Our courses are held remotely for researchers from all over the world, with disciplines ranging from academia to business, non-profit organizations, and government. We invite you to join one of our over 20 livestream seminars held this spring via Zoom. If you cannot attend live, you can participate asynchronously by watching recorded videos of each session. Learn topics like:

Marginal Structural Models with Daniel Westreich on March 3-5. This seminar is an introduction to marginal structural models (MSMs), which are increasingly used for causal inference in observational data, from both a theoretical and applied standpoint.

GitHub for Data Analysis with Aaron Gullickson on March 15-17. This seminar will familiarize you with using git, a free, open-source distributed version control system, through GitHub and demonstrate how to integrate GitHub into a research workflow.

Propensity Score Analysis with Shenyang Guo on March 17-19. This seminar will teach you to evaluate the effects of treatments or interventions when using nonexperimental or observational data using propensity score analysis.

Quantile Regression with Lingxin Hao on March 24-26. This seminar introduces quantile regression (QR), a method that allows for more information on conditional distribution of the dependent variable than standard linear regression, and how they depend on the predictors.

Psychometrics with Matthew Diemer on April 7-9. Psychometrics is the science of how we measure the psychological attributes of people. This seminar emphasizes the conceptual understanding and application of psychometric principles.

Statistics with R with Andrew Miles on April 28-30. This course is designed as an introduction to R, a free and open-source package for statistical analysis widely used in the social, health, physical, and computational sciences, for those who are looking to use R for applied statistical tasks.

Advanced Machine Learning with Ross Jacobucci on May 5-7. This seminar builds off of our introductory Machine Learning course, covering advanced topics for researchers already familiar with topics like regularization in regression, cross-validation, and decision trees.

Please email for more information on any of our courses or to receive a discount.