Question

DATA 2

ID	X1	X2	X3	Y
A	0	2	4	9
B	1	0	8	10
C	0	1	0	5
D	1	1	0	1
E	0	0	8	10

CORRELATION MATRIX

	Y	X1	X2	X3
Y	1	?	-0.304	+0.889
X1	?	1	-0.327	0
X2	-0.304	-0.327	1	-0.598
X3	+0.889	0	-0.598	1

1. What is the sum of squares regression for the full model? (Correct answer is 58, please show me how to get there)

2. What is the residual error in using the full model to predict Y for ID C? (Correct answer is +1, please show me how to get there)

Answer 1

Correlation Matrix :

	Y	X1	X2	X3
Y	1.000	-0.3478	-0.3036	0.8890
X1	-0.3478	1.0000	-0.3273	0.000
X2	-0.3036	-0.3273	1.000	-0.5976
X3	0.8890	0.000	-0.5976	1.000

1)

the sum of squares regression for the full model = 58

( Use regression calculation in excel)

2)

Y bar = 3 - 2 X1 + X2 + X3

For C

X1 = 0, X2 = 1 and X3 = 0

Y bar = 3+1 = 4

and Y = 5 at C ( from given table )

ei = Y - Y bar = 5-4 = 1