Step 2 (D):

At this point we checked the relationship between the other (quantitative) variables included in the data set and case sales of eggs, but what about the qualitative variables. To explore this, we create a box plot of Cases for different levels of the variable First.Week (a variable that indicates whether an observation corresponds to the first week in a month). Make this graphic into a data visualization.
Question 10: (1) Create a box plot of Cases for different levels of the variable First.Week. (include in appendix). (2) What are the median and quartile values (approximately) shown in the boxplots? (3) Does First.Week appear to have an effect? What is that effect? (4) Can you think of a plausible reason why this effect might exist?

Answers: (2)   (3)   (4)

 
Having explored the data set, we now can make a Multiple Linear Regression Model BUT first we want to make sure the qualitative variables have an appropriate baseline category before we have R create the corresponding dummy variables. For the moment, we are not going to use the Month variable and just look at the remaining other variables making sure "Non Easter" for Easter and "No" for First.Week are the defaults/baseline level. Reorder these variables to do this.