What is the expected result for the number of heads obtained in this coin/dice flipping example?











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Suppose you roll one fair six-sided die and then flip as many coins as the number showing on the die. (For example, if the die shows 4, then you flip four coins.) Let Y be the number of heads obtained. Compute $E(Y)$.



So, $E(Y)=Sigma_{y=1}^{y=6}yP_{y}(y)$



We will define $X$ as the number on the die. Therefore:



$$E(Y)=sum_{y=1}^{y=6}yP_{y}(y)=sum_{y=0}^{y=6}sum_{x=1}^{x=6}(y)P(X=x,Y=y)=sum_{y=0}^{y=6}ysum_{x=1}^{x=6}(1/6)binom{x}{y}(1/2)^x$$



This inner equation is valid: $(1/6)binom{x}{y}(1/2)^x$



Basically, it says that if I roll a 3, and I get 1 head only, what is the probability of that occurring = $(1/6)text{[for the roll]}binom{3}{1}text{[from 3 rolls, we choose one head]}(1/2)^3=1/16$



Now, I need to simplify the above double sum, but I am not sure how to do it. The answer in my textbook is $7/4$, but it does not show steps. I think I am right until now, I just need help doing this summation.










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  • The double sum is finite? You just plug in the numbers? See here.
    – Mason
    6 hours ago










  • You can also use the "law of total expectation" $E[Y] = sum_{d=1}^6 E[Y|X=d]P[X=d]$.
    – Michael
    6 hours ago












  • @Michael well it's actually supposed to be $binom{x}{y}(1/2)^y(1/2)^{x-y}$, but I simplified it
    – K Split X
    6 hours ago










  • Oh you are right, I was misinterpreting $x$ (I will delete that comment). But that is a difficult way to solve the problem.
    – Michael
    5 hours ago












  • What is the simpliest way?
    – K Split X
    5 hours ago















up vote
1
down vote

favorite












Suppose you roll one fair six-sided die and then flip as many coins as the number showing on the die. (For example, if the die shows 4, then you flip four coins.) Let Y be the number of heads obtained. Compute $E(Y)$.



So, $E(Y)=Sigma_{y=1}^{y=6}yP_{y}(y)$



We will define $X$ as the number on the die. Therefore:



$$E(Y)=sum_{y=1}^{y=6}yP_{y}(y)=sum_{y=0}^{y=6}sum_{x=1}^{x=6}(y)P(X=x,Y=y)=sum_{y=0}^{y=6}ysum_{x=1}^{x=6}(1/6)binom{x}{y}(1/2)^x$$



This inner equation is valid: $(1/6)binom{x}{y}(1/2)^x$



Basically, it says that if I roll a 3, and I get 1 head only, what is the probability of that occurring = $(1/6)text{[for the roll]}binom{3}{1}text{[from 3 rolls, we choose one head]}(1/2)^3=1/16$



Now, I need to simplify the above double sum, but I am not sure how to do it. The answer in my textbook is $7/4$, but it does not show steps. I think I am right until now, I just need help doing this summation.










share|cite|improve this question






















  • The double sum is finite? You just plug in the numbers? See here.
    – Mason
    6 hours ago










  • You can also use the "law of total expectation" $E[Y] = sum_{d=1}^6 E[Y|X=d]P[X=d]$.
    – Michael
    6 hours ago












  • @Michael well it's actually supposed to be $binom{x}{y}(1/2)^y(1/2)^{x-y}$, but I simplified it
    – K Split X
    6 hours ago










  • Oh you are right, I was misinterpreting $x$ (I will delete that comment). But that is a difficult way to solve the problem.
    – Michael
    5 hours ago












  • What is the simpliest way?
    – K Split X
    5 hours ago













up vote
1
down vote

favorite









up vote
1
down vote

favorite











Suppose you roll one fair six-sided die and then flip as many coins as the number showing on the die. (For example, if the die shows 4, then you flip four coins.) Let Y be the number of heads obtained. Compute $E(Y)$.



So, $E(Y)=Sigma_{y=1}^{y=6}yP_{y}(y)$



We will define $X$ as the number on the die. Therefore:



$$E(Y)=sum_{y=1}^{y=6}yP_{y}(y)=sum_{y=0}^{y=6}sum_{x=1}^{x=6}(y)P(X=x,Y=y)=sum_{y=0}^{y=6}ysum_{x=1}^{x=6}(1/6)binom{x}{y}(1/2)^x$$



This inner equation is valid: $(1/6)binom{x}{y}(1/2)^x$



Basically, it says that if I roll a 3, and I get 1 head only, what is the probability of that occurring = $(1/6)text{[for the roll]}binom{3}{1}text{[from 3 rolls, we choose one head]}(1/2)^3=1/16$



Now, I need to simplify the above double sum, but I am not sure how to do it. The answer in my textbook is $7/4$, but it does not show steps. I think I am right until now, I just need help doing this summation.










share|cite|improve this question













Suppose you roll one fair six-sided die and then flip as many coins as the number showing on the die. (For example, if the die shows 4, then you flip four coins.) Let Y be the number of heads obtained. Compute $E(Y)$.



So, $E(Y)=Sigma_{y=1}^{y=6}yP_{y}(y)$



We will define $X$ as the number on the die. Therefore:



$$E(Y)=sum_{y=1}^{y=6}yP_{y}(y)=sum_{y=0}^{y=6}sum_{x=1}^{x=6}(y)P(X=x,Y=y)=sum_{y=0}^{y=6}ysum_{x=1}^{x=6}(1/6)binom{x}{y}(1/2)^x$$



This inner equation is valid: $(1/6)binom{x}{y}(1/2)^x$



Basically, it says that if I roll a 3, and I get 1 head only, what is the probability of that occurring = $(1/6)text{[for the roll]}binom{3}{1}text{[from 3 rolls, we choose one head]}(1/2)^3=1/16$



Now, I need to simplify the above double sum, but I am not sure how to do it. The answer in my textbook is $7/4$, but it does not show steps. I think I am right until now, I just need help doing this summation.







probability summation binomial-distribution expected-value






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asked 6 hours ago









K Split X

4,0521031




4,0521031












  • The double sum is finite? You just plug in the numbers? See here.
    – Mason
    6 hours ago










  • You can also use the "law of total expectation" $E[Y] = sum_{d=1}^6 E[Y|X=d]P[X=d]$.
    – Michael
    6 hours ago












  • @Michael well it's actually supposed to be $binom{x}{y}(1/2)^y(1/2)^{x-y}$, but I simplified it
    – K Split X
    6 hours ago










  • Oh you are right, I was misinterpreting $x$ (I will delete that comment). But that is a difficult way to solve the problem.
    – Michael
    5 hours ago












  • What is the simpliest way?
    – K Split X
    5 hours ago


















  • The double sum is finite? You just plug in the numbers? See here.
    – Mason
    6 hours ago










  • You can also use the "law of total expectation" $E[Y] = sum_{d=1}^6 E[Y|X=d]P[X=d]$.
    – Michael
    6 hours ago












  • @Michael well it's actually supposed to be $binom{x}{y}(1/2)^y(1/2)^{x-y}$, but I simplified it
    – K Split X
    6 hours ago










  • Oh you are right, I was misinterpreting $x$ (I will delete that comment). But that is a difficult way to solve the problem.
    – Michael
    5 hours ago












  • What is the simpliest way?
    – K Split X
    5 hours ago
















The double sum is finite? You just plug in the numbers? See here.
– Mason
6 hours ago




The double sum is finite? You just plug in the numbers? See here.
– Mason
6 hours ago












You can also use the "law of total expectation" $E[Y] = sum_{d=1}^6 E[Y|X=d]P[X=d]$.
– Michael
6 hours ago






You can also use the "law of total expectation" $E[Y] = sum_{d=1}^6 E[Y|X=d]P[X=d]$.
– Michael
6 hours ago














@Michael well it's actually supposed to be $binom{x}{y}(1/2)^y(1/2)^{x-y}$, but I simplified it
– K Split X
6 hours ago




@Michael well it's actually supposed to be $binom{x}{y}(1/2)^y(1/2)^{x-y}$, but I simplified it
– K Split X
6 hours ago












Oh you are right, I was misinterpreting $x$ (I will delete that comment). But that is a difficult way to solve the problem.
– Michael
5 hours ago






Oh you are right, I was misinterpreting $x$ (I will delete that comment). But that is a difficult way to solve the problem.
– Michael
5 hours ago














What is the simpliest way?
– K Split X
5 hours ago




What is the simpliest way?
– K Split X
5 hours ago










1 Answer
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If $D$ is the result of the die-throw, $E(Y) = sum_{d=1}^6 E(Y|D=d)P(D=d)$.



Clearly $E(Y|D=d)= frac{d}{2}$. So we are left with $$E(Y) = sum_{d=1}^6 frac{1}{6}frac{d}{2} = frac{1}{12}sum_{d=1}^6 d = frac{21}{12}$$






share|cite|improve this answer





















  • Sorry, I have not learned this conditional expectation yet, but regardless, how did you get $d/2$? Is it just the probability of a head?
    – K Split X
    5 hours ago






  • 1




    @KSplitX binomial expectation is nr of trials time chance of success.
    – Henno Brandsma
    5 hours ago











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1 Answer
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1 Answer
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active

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up vote
2
down vote













If $D$ is the result of the die-throw, $E(Y) = sum_{d=1}^6 E(Y|D=d)P(D=d)$.



Clearly $E(Y|D=d)= frac{d}{2}$. So we are left with $$E(Y) = sum_{d=1}^6 frac{1}{6}frac{d}{2} = frac{1}{12}sum_{d=1}^6 d = frac{21}{12}$$






share|cite|improve this answer





















  • Sorry, I have not learned this conditional expectation yet, but regardless, how did you get $d/2$? Is it just the probability of a head?
    – K Split X
    5 hours ago






  • 1




    @KSplitX binomial expectation is nr of trials time chance of success.
    – Henno Brandsma
    5 hours ago















up vote
2
down vote













If $D$ is the result of the die-throw, $E(Y) = sum_{d=1}^6 E(Y|D=d)P(D=d)$.



Clearly $E(Y|D=d)= frac{d}{2}$. So we are left with $$E(Y) = sum_{d=1}^6 frac{1}{6}frac{d}{2} = frac{1}{12}sum_{d=1}^6 d = frac{21}{12}$$






share|cite|improve this answer





















  • Sorry, I have not learned this conditional expectation yet, but regardless, how did you get $d/2$? Is it just the probability of a head?
    – K Split X
    5 hours ago






  • 1




    @KSplitX binomial expectation is nr of trials time chance of success.
    – Henno Brandsma
    5 hours ago













up vote
2
down vote










up vote
2
down vote









If $D$ is the result of the die-throw, $E(Y) = sum_{d=1}^6 E(Y|D=d)P(D=d)$.



Clearly $E(Y|D=d)= frac{d}{2}$. So we are left with $$E(Y) = sum_{d=1}^6 frac{1}{6}frac{d}{2} = frac{1}{12}sum_{d=1}^6 d = frac{21}{12}$$






share|cite|improve this answer












If $D$ is the result of the die-throw, $E(Y) = sum_{d=1}^6 E(Y|D=d)P(D=d)$.



Clearly $E(Y|D=d)= frac{d}{2}$. So we are left with $$E(Y) = sum_{d=1}^6 frac{1}{6}frac{d}{2} = frac{1}{12}sum_{d=1}^6 d = frac{21}{12}$$







share|cite|improve this answer












share|cite|improve this answer



share|cite|improve this answer










answered 5 hours ago









Henno Brandsma

100k344107




100k344107












  • Sorry, I have not learned this conditional expectation yet, but regardless, how did you get $d/2$? Is it just the probability of a head?
    – K Split X
    5 hours ago






  • 1




    @KSplitX binomial expectation is nr of trials time chance of success.
    – Henno Brandsma
    5 hours ago


















  • Sorry, I have not learned this conditional expectation yet, but regardless, how did you get $d/2$? Is it just the probability of a head?
    – K Split X
    5 hours ago






  • 1




    @KSplitX binomial expectation is nr of trials time chance of success.
    – Henno Brandsma
    5 hours ago
















Sorry, I have not learned this conditional expectation yet, but regardless, how did you get $d/2$? Is it just the probability of a head?
– K Split X
5 hours ago




Sorry, I have not learned this conditional expectation yet, but regardless, how did you get $d/2$? Is it just the probability of a head?
– K Split X
5 hours ago




1




1




@KSplitX binomial expectation is nr of trials time chance of success.
– Henno Brandsma
5 hours ago




@KSplitX binomial expectation is nr of trials time chance of success.
– Henno Brandsma
5 hours ago


















 

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