Here are 4 models:

- Model 1: \(R^2 = 0.40,~AIC=110,~based~on~2~predictors\)
- Model 2: \(R^2 = 0.42,~AIC=105,~based~on~3~predictors\)
- Model 3: \(R^2 = 0.49,~AIC=102,~based~on~4~predictors\)
- Model 4: \(R^2 = 0.52,~AIC=110,~based~on~8~predictors\)

Please use the "redwines.csv" dataset in RStudio Cloud for the following prompts. Fit a logistic regression model to predict whether a wine is classified as good (Y=1) vs. not good (Y=0) from the variable alcohol alone.

Perform a formal hypothesis test to determine whther the 2 extra predictors in the model with alcohol, residual.sugar, and fixed.acidity (3 predictors) provide significantly better predictive power than the model using alcohol alone.