FURTHER INFORMATION ABOUT R-EXERCISE 2: Data: We will use the dataset "MASchools included in the package "AER". The dataset contains data on test performance, school characteristics and student demographic backgrounds for school districts in Massachusetts. (The lectures use a similar dataset for schools in CA.) For the questions in this exercise, therefore, you should load the dataset "MASchools" via: > data("MASchools", package="AER") There are alternative ways to load the data in R. In tutorial sessions for example, we loaded the package first and then loaded the data. R-tips: You might want to attach the dataset via: >attach(MASchools) You do not need to attach the dataset for this assessment. By attaching the dataset, however, you do not have to specify to which datasot the variables belong when you use them For examplo, suppose you want to get summary statistics of the variable salary. Then, before attaching the dataset, you have to do thin via > summary(MASchoolsStolary) But, once you attach the dataset "MASchools", you can do the same thing simply by >summary(salary) The command attach() is useful when you work with many variables. When you do not need the dataset anymore, you can detach it via: > detach(MASchools) 1 points D- QUESTION 5 Note that this exercise replicates Section 5.3 in Stock and Watson, but with the MA data instead of CA data. Hence, it would be helpful to read the section once again. Generate a new variable Din R that equals either Oor 1. depending on whether the student-teacher ratio is less than 17. i.e. (1 if the student - teacher ratio in th district