Conditional expectation and partitioning

In summary: I still don't understand why you're doing this … :confused:As I said, each family is independent, so just add the expectation for each family, i = 1 to n.So for family i, the expected number of girls is … ?I also don't know how to find the expected number of girls for each family. I am trying to use the formula E(X) = ∑ x
  • #1
Kate2010
146
0

Homework Statement


I'm told that of n couples, each of whom have at least one child, with couples procreating independently and no limits on family size, births single and independent, and for the ith couple the probability of a boy is p_i and of a girl is q_i with p_i + q_i = 1.

1. Show the expected family size if the ith couple stop when have had both sexes is 1/(p_iq_i) - 1.

2. If all n couples stop when have children of both sexes, what is the expected number of girls.

Homework Equations



E(X) = Sum(i=1..n) E(X|A_i) P(A_i)
E(X|A) = Sum(over x) xP(X=x|A)

The Attempt at a Solution



So for 1 I've got:
Let X be the number of births until a girl and boy
A1 = boy born 1st
A2 = girl born 1st
E(X) = E(X|A_1)P(A_1) + E(X|A_2)P(A_2) = (p_i/q_i) + (q_i/p_i) = 1/(p_iq_i) -2
Do I add 1 as I'm considering 2 births not 1?

For 2:
I'm not too sure how to go about this at all, I can use the second formula with X being the number of girls and A being that both sexes are born, but how do I know P(X=x|A)?

Earlier in the question I calculated the expected family size if the family stopped after a boy or a girl.

Thanks.
 
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  • #2
Hi Kate2010! :wink:
Kate2010 said:
… for the ith couple the probability of a boy is p_i and of a girl is q_i with p_i + q_i = 1.

1. Show the expected family size if the ith couple stop when have had both sexes is 1/(p_iq_i) - 1.

hmm … start again …

(with these problems, it's just a question of how to count …)

what's the probability that the first n-1 births are the same sex, and the nth birth is different? :smile:
 
  • #3
Would this be (p_i ^(n-1))q_i + (q_i ^(n-1))p_i ?
 
  • #4
Kate2010 said:
Would this be (p_i ^(n-1))q_i + (q_i ^(n-1))p_i ?

(have a sigma: ∑ and try using the X2 and X2 tags just above the Reply box :wink:)

Yup! :smile:

So the expected family size is … ?
 
  • #5
I still don't know where to go from here. Do I use E(X) = ∑ xP(X=x)?
 
  • #6
Yes. :smile:
 
  • #7
π²³ ∞ ° → ~ µ ρ σ Ω √ ∫ ≤ ≥ ± ∃ … · θ φ ψ ω Ω α β γ δ ∂ ∆ ∇ ε λ Λ Γ ô

E(X) = ∑ n (pin-1qi + qin-1pi)?

If this is correct, which I'm really not sure about, how do I do it?
 
  • #8
The left-hand part is qi times ∑ npin-1

how can you calculate that ∑ ? :smile:
 
  • #9
Would I do it as a geometris series which then differentiates to 1/(1-pi)2?

So it would be altogether qi/(1-pi)2 + pi/(1-qi)2 , but this equals 1?
 
  • #10
(i'm going out for the evening now, so this is my last post for some hours)

I haven't checked it properly, but did you take care to start your ∑ pn from the right point (ie does it start at n = 0, n = 1, or n = 2) ?
 
  • #11
I'm sorry I'm still struggling with this question.
I have qi∑ npin-1 + pi∑ nqin-1
These are geometric sums so can I use the formula ∑ (to infinity) xn = 1/(1-x) so ∑ (to infinity) nxn-1 = d/dx(1/(1-x)) = 1/(1-x)2 . However, I'm confused about what I'm summing from and 2. Am I summing from n=2 to infinity?
 
  • #12
Kate2010 said:
… I'm confused about what I'm summing from and 2. Am I summing from n=2 to infinity?

oh no, this is long and complicated and i don't want to have to write it all out myself …

you write it all out, including the ∫s and the ∑n=?s and i'll check it :smile:
 
  • #13
I want qi∑[tex]^{n=infinity}_{2}[/tex] npin-1 + pi∑[tex]^{n=infinity}_{2}[/tex] nqin-1

∑[tex]^{infinity}[/tex] xn= 1/(1-x) so ∑[tex]^{infinity}[/tex] nxn-1[/SUP = 1/(1-x)2

So qi∑[tex]^{infinity}_{n=1}[/tex] npin-1 + pi∑[tex]^{infinity}_{n=1}[/tex] nqin-1 = qi/(1-pi)2 + pi/(1-qi)2 = 1/qi + 1/pi = 1/piqi

I now need to subtract the sum to 1 of each, i.e. qi∑[tex]^{n=1}_{1}[/tex] npin-1 + pi∑[tex]^{n=1}_{1}[/tex] nqin-1 = 1+1 = 2

So I get 1/piqi -2, but I wanted 1/piqi -1.

I've only done discrete random variable so far and have not used [tex]\int[/tex] in probability.
 
Last edited:
  • #14
The third line down the sums should be the other way around but I can't make it format properly.
 
  • #15
(have an infinity: ∞ :wink:)
Kate2010 said:
I now need to subtract the sum to 1 of each, i.e. qi∑[tex]^{n=1}_{1}[/tex] npin-1 + pi∑[tex]^{n=1}_{1}[/tex] nqin-1 = 1+1 = 2

No, pi0 = qi0 = 1, so it's qi + pi = 1. :wink:

(and no need to say "the sum to 1", just say "the first term" !)
 
  • #16
Thank you so much!

For question 2:
If all n couples stop when have children of both sexes, what is the expected number of girls.

Do I use the forumula E(X|A) = [tex]\sum[/tex][tex]_{x}[/tex] xP(X=x) where X = number of girls and A = both sexes?

If so, I'm not sure how to calculate P(X=x), is it just 1/2? And would I sum from 2 to n (I'm considering n couples)?
 
  • #17
Kate2010 said:
For question 2:
If all n couples stop when have children of both sexes, what is the expected number of girls.

Do I use the forumula E(X|A) = [tex]\sum[/tex][tex]_{x}[/tex] xP(X=x) where X = number of girls and A = both sexes?

Each family is independent, so just add the expectation for each family, i = 1 to n.

Use a similar method as before … if the last birth is a girl, the number is 1, if it's a boy, the number is … ? :smile:
 
  • #18
Is P(X=x|A) always 1 as if there have been both sexes born there will always be a girl? Then it would just be [tex]\sum[/tex]x? But I don't know what to sum between.
 
  • #19
Kate2010 said:
Is P(X=x|A) always 1 as if there have been both sexes born there will always be a girl? Then it would just be [tex]\sum[/tex]x? But I don't know what to sum between.

I'm confused … where does A come into it? :confused:

Just use E(X) = ∑x xP(X=x)
 
  • #20
I thought I should use conditional expectation.

If I use E(X) = ∑x xP(X=x) with X being the being the number of girls, do I do ∑[tex]^{n}_{x=1}[/tex] xqi?

This would be qin(n+1)/2?
 

1. What is conditional expectation?

Conditional expectation is a statistical concept that measures the expected value of a random variable given the occurrence of a certain event or condition.

2. How is conditional expectation calculated?

Conditional expectation is calculated by taking the expected value of the random variable when the condition is met, and dividing it by the probability of the condition occurring.

3. What is meant by "partitioning" in conditional expectation?

Partitioning refers to dividing a sample space into mutually exclusive and exhaustive events, in order to calculate the conditional expectation for each event separately.

4. What is the importance of conditional expectation in statistics?

Conditional expectation is important in statistics because it allows for the analysis of data based on specific conditions or events, rather than just the overall distribution of the data. It can also be used to make predictions or forecasts based on certain conditions being met.

5. Can conditional expectation be negative?

Yes, conditional expectation can be negative. It simply represents the expected value of a random variable given a certain condition, and there is no restriction on the sign of the expected value.

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