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.
probability summation binomial-distribution expected-value
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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.
probability summation binomial-distribution expected-value
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
|
show 1 more comment
up vote
1
down vote
favorite
up vote
1
down vote
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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.
probability summation binomial-distribution expected-value
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
probability summation binomial-distribution expected-value
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
|
show 1 more comment
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
|
show 1 more comment
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 $$E(Y) = sum_{d=1}^6 frac{1}{6}frac{d}{2} = frac{1}{12}sum_{d=1}^6 d = frac{21}{12}$$
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
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
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 $$E(Y) = sum_{d=1}^6 frac{1}{6}frac{d}{2} = frac{1}{12}sum_{d=1}^6 d = frac{21}{12}$$
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
add a comment |
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 $$E(Y) = sum_{d=1}^6 frac{1}{6}frac{d}{2} = frac{1}{12}sum_{d=1}^6 d = frac{21}{12}$$
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
add a comment |
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 $$E(Y) = sum_{d=1}^6 frac{1}{6}frac{d}{2} = frac{1}{12}sum_{d=1}^6 d = frac{21}{12}$$
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 $$E(Y) = sum_{d=1}^6 frac{1}{6}frac{d}{2} = frac{1}{12}sum_{d=1}^6 d = frac{21}{12}$$
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
add a comment |
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
add a comment |
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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