Let’s use the Penguin dataset for our assignment. To learn more about the dataset, please visit:
https://allisonhorst.github.io/palmerpenguins/articles/intro.html
For this assignment, let us use ‘species’ as our outcome or the dependent variable.
- Logistic Regression with a binary outcome.
- The penguin dataset has ‘species’ column. Please check how many categories
you have in the species column. Conduct whatever data manipulation you need to do to be able to build a logistic regression with binary outcome. Please explain your reasoning behind your decision as you manipulate the outcome/dependent variable (species).
- Please make sure you are evaluating the independent variables appropriately in deciding which ones should be in the model.
- Provide variable interpretations in your model.
- The penguin dataset has ‘species’ column. Please check how many categories
- For your model from #1, please provide: AUC, Accuracy, TPR, FPR, TNR, FNR (20)
- Multinomial Logistic Regression.
- Please fit it a multinomial logistic regression where your outcome variable is
‘species’.
- Please be sure to evaluate the independent variables appropriately to fit your
best parsimonious model.
- Please be sure to interpret your variables in the model.
- Please fit it a multinomial logistic regression where your outcome variable is
- Extra credit: what would be some of the fit statistics you would want to evaluate for your model in question #3? Feel free to share whatever you can provide.

