(Ch14-prob set-Q9) please answer all questions by finding the missing numerical values. For question 3 answer options are: "passes" or "doesn't pass". Answer options for question 6 is: less than or equal to 14/ between 10&14/ 0/ less than or equal to 10

Student Year in College Course Work Hours per Class Freshman (1) 7 N Sophomore (2) Junior (3) NN Senior (4) A scatter plot of the sample data is shown here (blue circle symbols). The lin + 6 is shown in orange + ( NZ. My) HOURS YEAR Think about how close the line Y = -X + 6 is to the sample points. Look at the graph and find each point's vertical distance from the line. If the point sits above the line, the distance is positive; if the point sits below the line, the distance is negative. The sum of the vertical distances between the sample points and the orange line is 1 - and the sum of the squared vertical distances between the sample points and the orange line is On the graph, place the black point (X symbol) on the graph to plot the point (Mx, My), where Mx is the mean year for the four students (1, 2, 3, and 4) in the sample and My is the mean hours of course work per class for the four students (7. 7, 2, and 2) in the sample. Then use the green line (triangle symbols) to plot the line that has the same slope as (is parallel to) the line Y = -X + 6, but with the additional property that the vertical distances between the points and the line sum to 0. To plot the line, drag the green line onto the graph. Move the green triangles to adjust the slope. The line you just plotted through the point (Mx. My). The sum of the squared vertical distances between the sample points and the line that you just plotted is_ Which of the following describes the plotted line with the smallest total squared error?- OY--X+6 Neither-the two lines fit the data equally well The line you plotted that has a sum of the distances equal to 0 Suppose you fit the regression line to the four sample points on the graph. On the basis of your work so far, being as specific as you can be, you know that the total squared error is