This preview shows pages 1–2. Sign up to view the full content.
This preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
Unformatted text preview: N ( , ) where = 1 /n ( n1) /n1 /n 1 /n1 /n ( n1) /n 1 /n . . . . . . . . . . . . . . .1 /n1 /n ( n1) /n . By a theorem from last lecture (Theorem V.7.2), we conclude from the form of that X and ( X 1X, . . . , X nX ) are independent normal random vectors. It now follows from the transformation theorem (Theorem I.2.1 on page 23) that since X = ( X 1X, . . . , X nX ) and X are independent, so too are X and X X = n X i =1 ( X iX ) 2 . This now implies that X and S 2 are independent....
View
Full
Document
This note was uploaded on 03/26/2012 for the course STAT 351 taught by Professor Michaelkozdron during the Fall '08 term at University of Regina.
 Fall '08
 MichaelKozdron
 Statistics, Probability, Variance

Click to edit the document details