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Regression tutorials

There are three learnr tutorials in this directory:

  • tutorial-intro-lm introduces the lm function as applied to simple linear regression and basics of linear regression modeling. The tidy and glance functions from the broom package is also introduced here. Interpretation of coefficient estimates and statistical inference are briefly discussed.
  • tutorial-diag-pred-augment introduces multiple linear regression, as well as the augment function from broom. Interpretation of coefficient estimates and statistical inference are briefy discussed, as well as interaction terms and corresponding interpretations. Finally, we use augment and ggplot to evaluate model diagnostics.
  • tutorial-logistic introduces logistic regression as a way to create a model for binary outcomes. This tutorial also makes heavy use of the broom package.

The beijing.csv dataset is used for the linear model tutorials; the pokemon.csv dataset is used for the logistic regression tutorial.