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Unformatted text preview: & n x x = 6 5 35 = = & n y y = 7 1 & = ( ) ( ) ( ) 8 3 80 30 2 = = & &x x y y x x = 0.375 . & = x y 1 & = 7 ( 0.375 ) 6 = 4.75 . The leastsquares regression line: y = 4.75 + 0.375 x . x y y y y e = 2 e 0 4 4.75 0.75 0.5625 4 7 6.25 0.75 0.5625 6 6 7 1 1.0000 8 10 7.75 2.25 5.0625 12 8 9.25 1.25 1.5625 Total 0 8.75 RSS = ( ) & &= 2 2 i i i y y e = 8.75 . ( ) &= 2 2 1 & i i y y n = 5 75 . 8 = 1.75 . 75 . 1 & = 1.3229 . ( ) &= 2 2 2 1 i i e y y n s = 3 75 . 8 2.916667 . 916667 . 2 = e s 1.7078 . 20 75 . 8 2 1= R = 0.5625 . 56.25%...
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This note was uploaded on 02/10/2009 for the course STAT 420 taught by Professor Stepanov during the Spring '08 term at University of Illinois at Urbana–Champaign.
 Spring '08
 STEPANOV
 Statistics

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