Structural Equation Modeling Short Course 2019
June 19 - 21, 2019
9:00am - 5:00pm
Cornell University
Structural Equation Modeling (SEM) provides a general framework for examining complex relationships between variables. This hands-on course will cover the theory and methodology of SEM. Topics include path analysis, exploratory and confirmatory factor analysis, and regression with latent variables.
Who should attend? The course is aimed at researchers with no previous experience in SEM but who would like to confidently apply these methods to their own research.
See
http://cscu.cornell.edu/workshops/SEM_2019.php for more details.
Machine Learning Short Course 2019
August 5 - 7, 2019
9:00am - 5:00pm
Cornell University
This introductory hands-on course will introduce attendees to the major concepts of machine learning and cover the most commonly used methods. The course will focus heavily on the application and implementation of machine learning techniques.
Who should attend? Researchers from all fields who are interested in learning what machine learning is and how it could be useful in their research. No previous experience with machine learning is necessary, but familiarity with linear regression will be helpful.
See https://www.cscu.cornell.edu/workshops/ML_2019.php for more details.
------------------------------
--------------------------------
Stephen Parry
Statistical Consultant
Cornell Statistical Consulting Unit
Cornell University
--------------------------------
------------------------------