# 884067 262 2 number of 4 213a r 0903383 code for

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Unformatted text preview: . 2.53.Y i Yes, Xo.=niβ0 +1 iπσ 2 − 1 −1 σ 2 (Yi − β0 − β1 Xi2) g (Xi ) .54 − 5 ni = =1 2 , n exp 2 2.57. a. √ 2.53. a. L = exp − 2 (Yi − β0 − β1 Xi ) g (Xi ) 2 2σ =1 b. Yi − 2 − 5iXi = 2πσn , i Prob. 2.58 2-7 2.58. If ρ12 = 0, (2.74) becomes: 2-7 b. f (Y1 , Y2 ) = 1 1 exp − 2πσ1 σ2 2 1 1 Y1 − µ1 exp − 2 σ1 2πσ1 = f1 (Y1 ) · f2 (Y2 ) =√ 2.59. a. L= n 1 i=1 2πσ1 σ2 1 − ρ2 12 −2ρ12 ( Y1 − µ1 σ1 2 ·√ × exp{− 2 + Y2 − µ2 σ2 2 1 1 Y2 − µ2 exp − 2 σ2 2πσ2 Yi1 − µ1 2 1 [( ) 2 2(1 − ρ12 ) σ1 Yi1 − µ1 Yi2 − µ2 Yi2 − µ2 2 )( )+( ) ]} 2 W4315 – Linear Regression Models Homework...
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## This note was uploaded on 10/29/2012 for the course STAT W4315 taught by Professor Martinalindquist during the Spring '12 term at Columbia.

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