If the SSR X2 X1 to denote the extra sum of squares for adding X2 to a regression model alreday having X1 as the only predictor, which of the following statement is true? A. SSR(X3|X1,X2) = SSE (X1,X2) – SSE (X1,X2,X3)
B. SSR(X3|X1,X2) = SSR (X1,X2) – SSR(X1,X2,X3)
C. SSR(X3|X1,X2) = SSE (X3) – SSR (X1,X2)
D. SSR(X3|X1,X2) = SSR (X2|X3)

you forgot an image

step-by-step explanation:

it’s supposed to be -4+45=41

step-by-step explanation:

in geometry, parallel lines are lines in a plane which do not meet; that is, two lines in a plane that do not intersect or touch each other at any point are said to be parallel. by extension, a line and a plane, or two planes, in three-dimensional euclidean space that do not share a point are said to be parallel.

answer: cos [   arcsin (3/5) - arccos (1/2) ] =

step-by-step explanation: × = 3/5 = 0.6--> x = 36.87 and x = 180 - 36.87 = 143.13 deg

cos y = 1/2 --> y = +- 60 deg a. cos (x - y) = cos (143.13 - 60) = cos 83,13  

=

0.12

b. cos (36.87 - 60) = cos (-23.23) = 0.92