Key topics

Readings

These questions cover materials in:

Questions

Question 1

Instructions

Consider a scenario in which you have analyzed a data set that has lots of predictor variables.

You’ve built a multiple regression model, with many predictors, that explains a large amount of the variability in the data, i.e. it has a high \(R^2\) value.

Short essay: 3 pts

  • In a paragraph, describe a hypothetical analysis like the one above in which your best model, from the perspective of maximizing the R^2 may not be a good model from the perspective of understanding or explaining your data.

Question 2

Instructions

Consider the following variables in the Palmer penguins dataset:

  • Body mass (in grams)
  • Flipper length (in millimeters)
  • Sex (male/female)
  • Age (years)
  • Species (Gentoo, Chinstrap, or Adelie)

Multiple choice: 1 pt

  • Which of the variables above would be an appropriate response variable for a logistic regression?

Question 3

Instructions

Review Gardener’s description of beta coefficients (chapter 11.1). These are also known as standardized beta coefficients.

short answer: 2 pts

  • How are standardized beta coefficients different from the model slope coefficients?
  • What questions can you answer using the standardized beta coefficients?

Submit to Moodle

These questions are for your reference, the same questions will appear in the assignment page on Moodle.

You should do your work outside of Moodle, saving your answers in a document and/or R script file.

When you are ready to submit your answers, you can paste your complete responses in the corresponding Moodle question entries for the assignment.