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Unformatted text preview: /I ( ). 10 . 4 a. Write X i Y i X 2 i = X i ( X i + i ) X 2 i = 1 + X i i X 2 i . From normality and independence E X i i = 0 , Var X i i = 2 ( 2 + 2 ) , E X 2 i = 2 + 2 , Var X 2 i = 2 2 (2 2 + 2 ) , and Cov( X i ,X i i ) = 0. Applying the formulas of Example 5.5.27, the asymptotic mean and variance are E X i Y i X 2 i 1 and Var X i Y i X 2 i n 2 ( 2 + 2 ) [ n ( 2 + 2 )] 2 = 2 n ( 2 + 2 ) b. Y i X i = + i X i with approximate mean and variance 2 / ( n 2 )....
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This note was uploaded on 02/03/2012 for the course STA 1014 taught by Professor Dr.hackney during the Spring '12 term at UNF.
 Spring '12
 Dr.Hackney
 Statistics, Variance

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