A college bookstore must order books two months before each semester starts. They believe that the number of books that will ultimately be sold for any particular course is related to the number of students registered for the course when the books are ordered. They would like to develop a linear regression equation to help plan how many books to order. From past records, the bookstore obtains the number of students registered, X, and the number of books actually sold for a course, Y, for 12 different semesters. These data are below. Semesterstudents books 32 36 28 35 1 28 35 39 30 30 31 4. 34 30 29 7 31 38 36 38 29 26 38 33 8. 10 34 11 30 12 25 1. Conduct a simple linear regression to find the slope and intercept. The regression equation that you calculated is Y= ( Select ] [ Select ] 2. What percentage of variation in the data can be explained by the linear model? ( Select] 3. Conduct hypothesis test to verify if the slope can be considered equal to 0. The t-statistic is [ Select ) . The p-value is [ Select ] thus we can conclude that [ Select] 4. Based on the regression model, how many books can be expected to be sold if the class size next semester is expected to be 30 students? Answer: ( Select) 3) 61