4127033 82 1 04127033 2001717 conclude 2637123 if

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Unformatted text preview: E (b0 ) = E (Y b1 X ) = E (Y ) n 1X ¯ = E (Yi ) 1X n E (b0 ) = 0 ¯ 1X i=1 = n 1X ( n 0 + 1 Xi ) ¯ 1X − : ρ12 = 0. H0 : ρ12 = 0,1 Ha(−0.8657217) t = (−0.4127033 82)/ 1 − (−0.4127033) = 2.001717, conclude 2.637123. If |t∗ |conclude Ha .conclude HHaotherwise Ha . H , otherwise, ≤ 2.637123 Conclude 0 , . 2.48.−4.102897, t(.995; 82) = 0 a. −0.4127033 Conclude Ha . √ 2.48. a.b. −H0 : ρ12 = 0, Ha : ρ12 = 0. t∗ = (−0.4127033 82)/ 1 − (−0.4127033)2 = 0.4127033 W4315 – Linear Regression Models Fall 2011 √ 2.49. a. - Solutions 4 ρ12 = t 995; ρ12 2. 0. t∗ If |t∗ 0 ≤ 2.637123 conclude U 0 ,.4127033) = − b. H0 Homework 2 -0.42...
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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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