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Linear regression analysis in Python
January 27 @ 3:30 pm - 5:00 pm
Rackham Building, Earl Lewis Room, 3rd Floor East
This workshop will cover regression analysis using linear models and least squares in Python. We will discuss the goals and main use-cases for linear regression, and how to interpret a fitted linear model. We will then discuss methods for fitting more complex models with larger data sets, including the use of interactions, dummy-coding of categorical variables, and splines. Finally we will discuss some aspects of statistical inference and model selection for linear regression. Several case studies using open-access data sets will be used to illustrate the approaches.
Participants should bring a laptop if they want to work with the examples during the presentation, but this is optional.