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kurvmax
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Deriving Expectations (i.e. means)
I'm looking at my Introduction to Econometrics book and trying to figure out the derivations in the 2nd Chapter.
First, [tex]E(Y^{2}) = \sigma^{2}_{Y}+\mu^{2}_{Y}[/tex]
The derivation goes like this:
[tex]E(Y^{2}) = E{[(Y - \mu_{Y})+ \mu_{Y}]^{2}} = E[(Y- \mu_{Y})^2] + 2\mu_{Y}E(Y-\mu_{Y})+ \mu^{2}_{Y} = \sigma^{2}_{Y} + \mu^{2}_{Y}[/tex] because [tex]E(Y - \mu_{Y}) = 0[/tex]
If this last thing equals zero, then why doesn't everything but [tex]\mu^{2}_{Y}[/tex] drop out?
I'm looking at my Introduction to Econometrics book and trying to figure out the derivations in the 2nd Chapter.
First, [tex]E(Y^{2}) = \sigma^{2}_{Y}+\mu^{2}_{Y}[/tex]
The derivation goes like this:
[tex]E(Y^{2}) = E{[(Y - \mu_{Y})+ \mu_{Y}]^{2}} = E[(Y- \mu_{Y})^2] + 2\mu_{Y}E(Y-\mu_{Y})+ \mu^{2}_{Y} = \sigma^{2}_{Y} + \mu^{2}_{Y}[/tex] because [tex]E(Y - \mu_{Y}) = 0[/tex]
If this last thing equals zero, then why doesn't everything but [tex]\mu^{2}_{Y}[/tex] drop out?
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