Question

1. From the linear regression data used in Chapter 14.2 #3 and carried forward to #17: (40 points)

The sample data and regression coefficients were computed as follows

            

Item	1	2	3	4	5		Sums	Means
Yi	7	18	9	26	23		=83	= 16.6
Xi	2	6	9	13	20		=50	= 10

Warning the Xs and Ys are flipped from the way your textbook and my PowerPoint state. But this should not confuse you.

From this data above: The regression line has already been calculated as

= 7.6 +.9

1. Find the residual (Yi - for each of the 5 points in the regression, square them in the second row. (Similare to Table 14.3 in Textbook.)

Item	1	2	3	4	5		Sums
Yi -
(Yi -							SSE =

2. Find the Deviations between (Yi -   for each of the 5 point in the Y data. Then Square them below and take the sum. (Similar to Table 14.4 in textbook.)

Item			1	2	3	4	5		Sums
(Yi -
(Yi -									SST=

From the results above, calculate the following

3. SSR =

  D. The Coefficient of Determination, aka R² =

5. MSE =

Answer 1