Exercise

Evaluating the NYC SAT Scores Factorial Model

We've built our model, so we know what's next: model checking! We need to examine both if our outcome and our model residuals are normally distributed. We'll check the normality assumption using shapiro.test(). A low p-value means we can reject the null hypothesis that the sample came from a normally distributed population.

Let's carry out the requisite model checks for our 2^k factorial model, nyc_scores_factorial, which has been loaded for you.

Instructions

100 XP
  • Test the outcome Average_Score_SAT_Math from nyc_scores for normality using shapiro.test().
  • Set up a 2 by 2 grid for plots and plot the nyc_scores_factorial model object to create the residual plots.