Modeling and inference

Data Science with R

Author

Mine Çetinkaya-Rundel + Elijah Meyer

Slides

Title
Welcome
Language of models
Linear regression with a numerical predictor
Linear regression with a categorical predictor
Outliers in linear regression
Linear regression with multiple predictors
Main and interaction effects
Logistic regression
Clasification and decision errors
Overfitting and spending your data
Quantifying uncertainty
Bootstrapping
Hypothesis testing

Code alongs

Title
Modeling fish (Complete)
Modeling fish
Modeling loan interest rates (Complete)
Modeling loan interest rates
Building a spam filter (Complete)
Building a spam filter
Forest classification (Complete)
Forest classification
Bootstrapping Duke Forest houses (Complete)
Bootstrapping Duke Forest houses

Exercises

Title
Predicting cholesterol with simple linear regression
Predicting income level with logistic regression
Predicting NBA salaries with multiple linear regression
Quantifying uncertanity in the ICU