Normal Distribution: Sample Mean & Variance

[axe69]

ok guys , i need an answer to this question , use both moment generating function and cummulative function to show that z=(x(bar)-[tex]\mu[/tex])/([tex]\sigma[/tex]/[tex]\sqrt{n}[/tex]) if x(bar) is based on a random sample of size n from a normal([tex]\mu[/tex],[tex]\sigma[/tex]^2)

 

[Focus]

Sorry this question is rather vague. Do you wish to prove that a normalized normal is a normal (0,1)? The x(bar) is deceiving, as it usually means sample mean, in the case you are taking a sample mean then z is not a distribution.

 

[axe69]

mannaged to prove it ,and jst b4 the submition date ,thnx 4 you help