MHB Probability expectations with n

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The discussion revolves around calculating expected values using a discrete probability distribution function, specifically P{ξ = n} = (3/4)(1/4)^n. Participants clarify the application of the series sum for expected value calculations, leading to E{ξ} = 1/3 and E{(-3)ξ} = 3/7. Confusion arises regarding the coefficients in the series, particularly whether to use 3/4 or 1/4 in the calculations. After addressing the misunderstanding, the correct approach is confirmed, and gratitude is expressed for the assistance. The thread highlights the importance of careful application of series in probability calculations.
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I'm stuck on this question. I've done plenty of the questions with numbers etc but not sure how to deal with the n case for this one.

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Thank you :)
 

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Carla1985 said:
I'm stuck on this question. I've done plenty of the questions with numbers etc but not sure how to deal with the n case for this one.

View attachment 689

Thank you :)

If the discrete p.d.f. is...

$\displaystyle P \{ \xi = n \} = \frac{3}{4}\ (\frac{1}{4})^{n}$ (1)

... then, tacking into account that is...

$\displaystyle \sum_{n=0}^{\infty} n\ x^{n} = \frac{x} {(1-x)^{2}}$ (2)

... You obtain...

$\displaystyle E \{ \xi \} = \frac{3}{4}\ \sum_{n=0}^{\infty} n\ (\frac{1}{4})^{n} = \frac{\frac{3}{4}\ \frac{1}{4}}{(\frac{3}{4})^{2}} = \frac{1}{3}$ (3)

Regarding (ii) by definition is...

$\displaystyle E \{ (-3)^{\xi} \} = \frac{3}{4}\ \sum_{n=0}^{\infty} (-3)^{n}\ (\frac{1}{4})^{n} = \frac{3}{4} \frac{1}{1+\frac{3}{4}} = \frac{3}{7}$ (4)Kind regards$\chi$ $\sigma$
 
Last edited:
chisigma said:
... You obtain...

$\displaystyle E \{ \xi \} = \frac{3}{4}\ \sum_{n=0}^{\infty} n\ (\frac{1}{4})^{n} = \frac{\frac{3}{4}}{(\frac{3}{4})^{2}} = \frac{4}{3}$ (3)
Im confused by this part. If i use the series from the line above taking x to be 1/4 isn't it 1/4 on top instead of 3/4? or have i missed something?
Thanks for the help x
 
Carla1985 said:
Im confused by this part. If i use the series from the line above taking x to be 1/4 isn't it 1/4 on top instead of 3/4? or have i missed something?
Thanks for the help x

All right!... the mistake has been corrected... thak You very much!...

Kind regards

$\chi$ $\sigma$
 
Thats fab, thanks very much for the help x
 
The standard _A " operator" maps a Null Hypothesis Ho into a decision set { Do not reject:=1 and reject :=0}. In this sense ( HA)_A , makes no sense. Since H0, HA aren't exhaustive, can we find an alternative operator, _A' , so that ( H_A)_A' makes sense? Isn't Pearson Neyman related to this? Hope I'm making sense. Edit: I was motivated by a superficial similarity of the idea with double transposition of matrices M, with ## (M^{T})^{T}=M##, and just wanted to see if it made sense to talk...

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