Probability - Expectation value and Covariance
up vote
0
down vote
favorite
A group of $n = 10$ men exchange their gloves randomly (altogether there are 20 gloves).
Let $X_i$ be the random variable which attains the value 1 if the $i-th$ man got at least one of his gloves back and it attains the value 0 otherwise. Set $p = E(X_i)$ and $σ^2 = Var(X_i)$.
Observe that $p = frac{37}{190}$ and that $Var (X_i) = frac{5661}{190^2}$.
Let $b$ be the probability that for $ine j$ both the $i-th$ and $j-th$ men got at least one of their gloves back.
Show that $b = frac {1157}{{20 choose 2}{18 choose 2}}$.
1.) Let $X$ be the total number of men who received at least one of their gloves. Find $E(X)$.
2.) Calculate $Var(X).$ You may write it as an expression in $p$, $σ^2$ and $b.$
At first I just thought that $E(X)=np=10frac{37}{190}$ and then $Var(X)=npq=10cdot 37cdotfrac{153}{190^2}$ but now I am not sure about that, as the events do intersect: if someone takes gloves of someone else, then someone else has nothing to choose from. However, I do not know how to count these. Could you help me, please? Thanks
probability probability-distributions variance expected-value
add a comment |
up vote
0
down vote
favorite
A group of $n = 10$ men exchange their gloves randomly (altogether there are 20 gloves).
Let $X_i$ be the random variable which attains the value 1 if the $i-th$ man got at least one of his gloves back and it attains the value 0 otherwise. Set $p = E(X_i)$ and $σ^2 = Var(X_i)$.
Observe that $p = frac{37}{190}$ and that $Var (X_i) = frac{5661}{190^2}$.
Let $b$ be the probability that for $ine j$ both the $i-th$ and $j-th$ men got at least one of their gloves back.
Show that $b = frac {1157}{{20 choose 2}{18 choose 2}}$.
1.) Let $X$ be the total number of men who received at least one of their gloves. Find $E(X)$.
2.) Calculate $Var(X).$ You may write it as an expression in $p$, $σ^2$ and $b.$
At first I just thought that $E(X)=np=10frac{37}{190}$ and then $Var(X)=npq=10cdot 37cdotfrac{153}{190^2}$ but now I am not sure about that, as the events do intersect: if someone takes gloves of someone else, then someone else has nothing to choose from. However, I do not know how to count these. Could you help me, please? Thanks
probability probability-distributions variance expected-value
What's the definition of $b$? The expectation is correct, as it's just linearity. For the variance, consider the formula using the covariance, as it's not clear if the $X_i$ are independent
– Stockfish
Nov 19 at 10:59
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
A group of $n = 10$ men exchange their gloves randomly (altogether there are 20 gloves).
Let $X_i$ be the random variable which attains the value 1 if the $i-th$ man got at least one of his gloves back and it attains the value 0 otherwise. Set $p = E(X_i)$ and $σ^2 = Var(X_i)$.
Observe that $p = frac{37}{190}$ and that $Var (X_i) = frac{5661}{190^2}$.
Let $b$ be the probability that for $ine j$ both the $i-th$ and $j-th$ men got at least one of their gloves back.
Show that $b = frac {1157}{{20 choose 2}{18 choose 2}}$.
1.) Let $X$ be the total number of men who received at least one of their gloves. Find $E(X)$.
2.) Calculate $Var(X).$ You may write it as an expression in $p$, $σ^2$ and $b.$
At first I just thought that $E(X)=np=10frac{37}{190}$ and then $Var(X)=npq=10cdot 37cdotfrac{153}{190^2}$ but now I am not sure about that, as the events do intersect: if someone takes gloves of someone else, then someone else has nothing to choose from. However, I do not know how to count these. Could you help me, please? Thanks
probability probability-distributions variance expected-value
A group of $n = 10$ men exchange their gloves randomly (altogether there are 20 gloves).
Let $X_i$ be the random variable which attains the value 1 if the $i-th$ man got at least one of his gloves back and it attains the value 0 otherwise. Set $p = E(X_i)$ and $σ^2 = Var(X_i)$.
Observe that $p = frac{37}{190}$ and that $Var (X_i) = frac{5661}{190^2}$.
Let $b$ be the probability that for $ine j$ both the $i-th$ and $j-th$ men got at least one of their gloves back.
Show that $b = frac {1157}{{20 choose 2}{18 choose 2}}$.
1.) Let $X$ be the total number of men who received at least one of their gloves. Find $E(X)$.
2.) Calculate $Var(X).$ You may write it as an expression in $p$, $σ^2$ and $b.$
At first I just thought that $E(X)=np=10frac{37}{190}$ and then $Var(X)=npq=10cdot 37cdotfrac{153}{190^2}$ but now I am not sure about that, as the events do intersect: if someone takes gloves of someone else, then someone else has nothing to choose from. However, I do not know how to count these. Could you help me, please? Thanks
probability probability-distributions variance expected-value
probability probability-distributions variance expected-value
edited Nov 19 at 11:36
asked Nov 19 at 10:27
Daniel
83
83
What's the definition of $b$? The expectation is correct, as it's just linearity. For the variance, consider the formula using the covariance, as it's not clear if the $X_i$ are independent
– Stockfish
Nov 19 at 10:59
add a comment |
What's the definition of $b$? The expectation is correct, as it's just linearity. For the variance, consider the formula using the covariance, as it's not clear if the $X_i$ are independent
– Stockfish
Nov 19 at 10:59
What's the definition of $b$? The expectation is correct, as it's just linearity. For the variance, consider the formula using the covariance, as it's not clear if the $X_i$ are independent
– Stockfish
Nov 19 at 10:59
What's the definition of $b$? The expectation is correct, as it's just linearity. For the variance, consider the formula using the covariance, as it's not clear if the $X_i$ are independent
– Stockfish
Nov 19 at 10:59
add a comment |
1 Answer
1
active
oldest
votes
up vote
0
down vote
accepted
Your calculations of $p$, $sigma^2$ and $mathbb EX$ are okay.
Covariance is bilinear, so that by symmetry:
$$mathsf{Var}(X)=mathsf{Cov}(sum_{i=1}^{10}X_i,sum_{j=1}^{10}X_j)=sum_{i=1}^{10}sum_{j=1}^{10}mathsf{Cov}(X_i,X_j)=10mathsf{Var}(X_1)+90mathsf{Cov}(X_1,X_2)=$$$$10sigma^2+90(mathbb EX_1X_2-mathbb EX_1mathbb EX_2)=10sigma^{10}+90(P(X_1=X_2=1)-P(X_1=1)P(X_2=1))=$$$$10sigma^2+90(b-p^2)$$
Here $b=P(X_1=X_2=1)$ so it remains to find $P(X_1=X_2=1)$
edit:
Let $Z_{1}$ denote the number of gloves taken by person 1 that
belong to person 1.
Let $Y_{1}$ denote the number of gloves taken by person 1 that belong
to person 2.
Then:
$$Pleft(X_{1}=X_{2}=1right)=$$$$Pleft(X_{2}=1mid Z_{1}=2right)Pleft(Z_{1}=2right)+$$$$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=0right)Pleft(Z_{1}=1wedge Y_{1}=0right)+$$$$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=1right)Pleft(Z_{1}=1wedge Y_{1}=1right)$$
This with
$Pleft(X_{2}=1mid Z_{1}=2right)=1-Pleft(X_{2}=0mid Z_{1}=2right)=1-frac{16}{18}frac{15}{17}$
$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=0right)=1-Pleft(X_{2}=0mid Z_{1}=1wedge Y_{1}=0right)=1-frac{16}{18}frac{15}{17}$
$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=1right)=1-Pleft(X_{2}=0mid Z_{1}=1wedge Y_{1}=1right)=1-frac{17}{18}frac{16}{17}$
$Pleft(Z_{1}=2right)=frac{2}{20}frac{1}{19}$
$Pleft(Z_{1}=1wedge Y_{1}=0right)=frac{2}{20}frac{16}{19}+frac{16}{20}frac{2}{19}$
$Pleft(Z_{1}=1wedge Y_{1}=1right)=frac{2}{20}frac{2}{19}+frac{2}{20}frac{2}{19}$
So than P(X1=1|X2=1) is equal to probability of intersection of these events divided by p. But isn't the probability of intersection defined as b=1157/(190*153)?
– Daniel
Nov 19 at 12:06
I have made an edit (because finding $P(X_1=2mid X_1=1)$ was a bit more complicated than I thought). Does this help?
– drhab
Nov 19 at 12:41
I still do not understand it completely. I counted this: P(Z=1)=36/190 and P(Z=2)=1/190. P(X2=1∣Z=2)=(2*16+1)/153 But P(X2=1∣Z=1) makes me problem. I think that it is similar to problem above, just there are four cases when the first man picked one his glove and one glove of the second man, so that it is equal to 33-4=29. But then I got in total less than 1157. Could you tell me what is wrong, please?
– Daniel
Nov 19 at 15:57
Again I underestimated the complexity. I edited to provide a way to calculate $P(X_1=X_2=1)$. Do check me on mistakes, though.
– drhab
Nov 19 at 18:16
Thank you very much! I calculated it and I got 1289/((20C2)(18C2)). But it should be 1157/((20C2)(18C2)), according to the task. Do you think it might be just wrong?
– Daniel
Nov 19 at 19:12
|
show 2 more comments
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
accepted
Your calculations of $p$, $sigma^2$ and $mathbb EX$ are okay.
Covariance is bilinear, so that by symmetry:
$$mathsf{Var}(X)=mathsf{Cov}(sum_{i=1}^{10}X_i,sum_{j=1}^{10}X_j)=sum_{i=1}^{10}sum_{j=1}^{10}mathsf{Cov}(X_i,X_j)=10mathsf{Var}(X_1)+90mathsf{Cov}(X_1,X_2)=$$$$10sigma^2+90(mathbb EX_1X_2-mathbb EX_1mathbb EX_2)=10sigma^{10}+90(P(X_1=X_2=1)-P(X_1=1)P(X_2=1))=$$$$10sigma^2+90(b-p^2)$$
Here $b=P(X_1=X_2=1)$ so it remains to find $P(X_1=X_2=1)$
edit:
Let $Z_{1}$ denote the number of gloves taken by person 1 that
belong to person 1.
Let $Y_{1}$ denote the number of gloves taken by person 1 that belong
to person 2.
Then:
$$Pleft(X_{1}=X_{2}=1right)=$$$$Pleft(X_{2}=1mid Z_{1}=2right)Pleft(Z_{1}=2right)+$$$$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=0right)Pleft(Z_{1}=1wedge Y_{1}=0right)+$$$$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=1right)Pleft(Z_{1}=1wedge Y_{1}=1right)$$
This with
$Pleft(X_{2}=1mid Z_{1}=2right)=1-Pleft(X_{2}=0mid Z_{1}=2right)=1-frac{16}{18}frac{15}{17}$
$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=0right)=1-Pleft(X_{2}=0mid Z_{1}=1wedge Y_{1}=0right)=1-frac{16}{18}frac{15}{17}$
$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=1right)=1-Pleft(X_{2}=0mid Z_{1}=1wedge Y_{1}=1right)=1-frac{17}{18}frac{16}{17}$
$Pleft(Z_{1}=2right)=frac{2}{20}frac{1}{19}$
$Pleft(Z_{1}=1wedge Y_{1}=0right)=frac{2}{20}frac{16}{19}+frac{16}{20}frac{2}{19}$
$Pleft(Z_{1}=1wedge Y_{1}=1right)=frac{2}{20}frac{2}{19}+frac{2}{20}frac{2}{19}$
So than P(X1=1|X2=1) is equal to probability of intersection of these events divided by p. But isn't the probability of intersection defined as b=1157/(190*153)?
– Daniel
Nov 19 at 12:06
I have made an edit (because finding $P(X_1=2mid X_1=1)$ was a bit more complicated than I thought). Does this help?
– drhab
Nov 19 at 12:41
I still do not understand it completely. I counted this: P(Z=1)=36/190 and P(Z=2)=1/190. P(X2=1∣Z=2)=(2*16+1)/153 But P(X2=1∣Z=1) makes me problem. I think that it is similar to problem above, just there are four cases when the first man picked one his glove and one glove of the second man, so that it is equal to 33-4=29. But then I got in total less than 1157. Could you tell me what is wrong, please?
– Daniel
Nov 19 at 15:57
Again I underestimated the complexity. I edited to provide a way to calculate $P(X_1=X_2=1)$. Do check me on mistakes, though.
– drhab
Nov 19 at 18:16
Thank you very much! I calculated it and I got 1289/((20C2)(18C2)). But it should be 1157/((20C2)(18C2)), according to the task. Do you think it might be just wrong?
– Daniel
Nov 19 at 19:12
|
show 2 more comments
up vote
0
down vote
accepted
Your calculations of $p$, $sigma^2$ and $mathbb EX$ are okay.
Covariance is bilinear, so that by symmetry:
$$mathsf{Var}(X)=mathsf{Cov}(sum_{i=1}^{10}X_i,sum_{j=1}^{10}X_j)=sum_{i=1}^{10}sum_{j=1}^{10}mathsf{Cov}(X_i,X_j)=10mathsf{Var}(X_1)+90mathsf{Cov}(X_1,X_2)=$$$$10sigma^2+90(mathbb EX_1X_2-mathbb EX_1mathbb EX_2)=10sigma^{10}+90(P(X_1=X_2=1)-P(X_1=1)P(X_2=1))=$$$$10sigma^2+90(b-p^2)$$
Here $b=P(X_1=X_2=1)$ so it remains to find $P(X_1=X_2=1)$
edit:
Let $Z_{1}$ denote the number of gloves taken by person 1 that
belong to person 1.
Let $Y_{1}$ denote the number of gloves taken by person 1 that belong
to person 2.
Then:
$$Pleft(X_{1}=X_{2}=1right)=$$$$Pleft(X_{2}=1mid Z_{1}=2right)Pleft(Z_{1}=2right)+$$$$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=0right)Pleft(Z_{1}=1wedge Y_{1}=0right)+$$$$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=1right)Pleft(Z_{1}=1wedge Y_{1}=1right)$$
This with
$Pleft(X_{2}=1mid Z_{1}=2right)=1-Pleft(X_{2}=0mid Z_{1}=2right)=1-frac{16}{18}frac{15}{17}$
$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=0right)=1-Pleft(X_{2}=0mid Z_{1}=1wedge Y_{1}=0right)=1-frac{16}{18}frac{15}{17}$
$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=1right)=1-Pleft(X_{2}=0mid Z_{1}=1wedge Y_{1}=1right)=1-frac{17}{18}frac{16}{17}$
$Pleft(Z_{1}=2right)=frac{2}{20}frac{1}{19}$
$Pleft(Z_{1}=1wedge Y_{1}=0right)=frac{2}{20}frac{16}{19}+frac{16}{20}frac{2}{19}$
$Pleft(Z_{1}=1wedge Y_{1}=1right)=frac{2}{20}frac{2}{19}+frac{2}{20}frac{2}{19}$
So than P(X1=1|X2=1) is equal to probability of intersection of these events divided by p. But isn't the probability of intersection defined as b=1157/(190*153)?
– Daniel
Nov 19 at 12:06
I have made an edit (because finding $P(X_1=2mid X_1=1)$ was a bit more complicated than I thought). Does this help?
– drhab
Nov 19 at 12:41
I still do not understand it completely. I counted this: P(Z=1)=36/190 and P(Z=2)=1/190. P(X2=1∣Z=2)=(2*16+1)/153 But P(X2=1∣Z=1) makes me problem. I think that it is similar to problem above, just there are four cases when the first man picked one his glove and one glove of the second man, so that it is equal to 33-4=29. But then I got in total less than 1157. Could you tell me what is wrong, please?
– Daniel
Nov 19 at 15:57
Again I underestimated the complexity. I edited to provide a way to calculate $P(X_1=X_2=1)$. Do check me on mistakes, though.
– drhab
Nov 19 at 18:16
Thank you very much! I calculated it and I got 1289/((20C2)(18C2)). But it should be 1157/((20C2)(18C2)), according to the task. Do you think it might be just wrong?
– Daniel
Nov 19 at 19:12
|
show 2 more comments
up vote
0
down vote
accepted
up vote
0
down vote
accepted
Your calculations of $p$, $sigma^2$ and $mathbb EX$ are okay.
Covariance is bilinear, so that by symmetry:
$$mathsf{Var}(X)=mathsf{Cov}(sum_{i=1}^{10}X_i,sum_{j=1}^{10}X_j)=sum_{i=1}^{10}sum_{j=1}^{10}mathsf{Cov}(X_i,X_j)=10mathsf{Var}(X_1)+90mathsf{Cov}(X_1,X_2)=$$$$10sigma^2+90(mathbb EX_1X_2-mathbb EX_1mathbb EX_2)=10sigma^{10}+90(P(X_1=X_2=1)-P(X_1=1)P(X_2=1))=$$$$10sigma^2+90(b-p^2)$$
Here $b=P(X_1=X_2=1)$ so it remains to find $P(X_1=X_2=1)$
edit:
Let $Z_{1}$ denote the number of gloves taken by person 1 that
belong to person 1.
Let $Y_{1}$ denote the number of gloves taken by person 1 that belong
to person 2.
Then:
$$Pleft(X_{1}=X_{2}=1right)=$$$$Pleft(X_{2}=1mid Z_{1}=2right)Pleft(Z_{1}=2right)+$$$$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=0right)Pleft(Z_{1}=1wedge Y_{1}=0right)+$$$$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=1right)Pleft(Z_{1}=1wedge Y_{1}=1right)$$
This with
$Pleft(X_{2}=1mid Z_{1}=2right)=1-Pleft(X_{2}=0mid Z_{1}=2right)=1-frac{16}{18}frac{15}{17}$
$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=0right)=1-Pleft(X_{2}=0mid Z_{1}=1wedge Y_{1}=0right)=1-frac{16}{18}frac{15}{17}$
$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=1right)=1-Pleft(X_{2}=0mid Z_{1}=1wedge Y_{1}=1right)=1-frac{17}{18}frac{16}{17}$
$Pleft(Z_{1}=2right)=frac{2}{20}frac{1}{19}$
$Pleft(Z_{1}=1wedge Y_{1}=0right)=frac{2}{20}frac{16}{19}+frac{16}{20}frac{2}{19}$
$Pleft(Z_{1}=1wedge Y_{1}=1right)=frac{2}{20}frac{2}{19}+frac{2}{20}frac{2}{19}$
Your calculations of $p$, $sigma^2$ and $mathbb EX$ are okay.
Covariance is bilinear, so that by symmetry:
$$mathsf{Var}(X)=mathsf{Cov}(sum_{i=1}^{10}X_i,sum_{j=1}^{10}X_j)=sum_{i=1}^{10}sum_{j=1}^{10}mathsf{Cov}(X_i,X_j)=10mathsf{Var}(X_1)+90mathsf{Cov}(X_1,X_2)=$$$$10sigma^2+90(mathbb EX_1X_2-mathbb EX_1mathbb EX_2)=10sigma^{10}+90(P(X_1=X_2=1)-P(X_1=1)P(X_2=1))=$$$$10sigma^2+90(b-p^2)$$
Here $b=P(X_1=X_2=1)$ so it remains to find $P(X_1=X_2=1)$
edit:
Let $Z_{1}$ denote the number of gloves taken by person 1 that
belong to person 1.
Let $Y_{1}$ denote the number of gloves taken by person 1 that belong
to person 2.
Then:
$$Pleft(X_{1}=X_{2}=1right)=$$$$Pleft(X_{2}=1mid Z_{1}=2right)Pleft(Z_{1}=2right)+$$$$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=0right)Pleft(Z_{1}=1wedge Y_{1}=0right)+$$$$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=1right)Pleft(Z_{1}=1wedge Y_{1}=1right)$$
This with
$Pleft(X_{2}=1mid Z_{1}=2right)=1-Pleft(X_{2}=0mid Z_{1}=2right)=1-frac{16}{18}frac{15}{17}$
$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=0right)=1-Pleft(X_{2}=0mid Z_{1}=1wedge Y_{1}=0right)=1-frac{16}{18}frac{15}{17}$
$Pleft(X_{2}=1mid Z_{1}=1wedge Y_{1}=1right)=1-Pleft(X_{2}=0mid Z_{1}=1wedge Y_{1}=1right)=1-frac{17}{18}frac{16}{17}$
$Pleft(Z_{1}=2right)=frac{2}{20}frac{1}{19}$
$Pleft(Z_{1}=1wedge Y_{1}=0right)=frac{2}{20}frac{16}{19}+frac{16}{20}frac{2}{19}$
$Pleft(Z_{1}=1wedge Y_{1}=1right)=frac{2}{20}frac{2}{19}+frac{2}{20}frac{2}{19}$
edited Nov 20 at 9:39
answered Nov 19 at 11:37
drhab
95.7k543126
95.7k543126
So than P(X1=1|X2=1) is equal to probability of intersection of these events divided by p. But isn't the probability of intersection defined as b=1157/(190*153)?
– Daniel
Nov 19 at 12:06
I have made an edit (because finding $P(X_1=2mid X_1=1)$ was a bit more complicated than I thought). Does this help?
– drhab
Nov 19 at 12:41
I still do not understand it completely. I counted this: P(Z=1)=36/190 and P(Z=2)=1/190. P(X2=1∣Z=2)=(2*16+1)/153 But P(X2=1∣Z=1) makes me problem. I think that it is similar to problem above, just there are four cases when the first man picked one his glove and one glove of the second man, so that it is equal to 33-4=29. But then I got in total less than 1157. Could you tell me what is wrong, please?
– Daniel
Nov 19 at 15:57
Again I underestimated the complexity. I edited to provide a way to calculate $P(X_1=X_2=1)$. Do check me on mistakes, though.
– drhab
Nov 19 at 18:16
Thank you very much! I calculated it and I got 1289/((20C2)(18C2)). But it should be 1157/((20C2)(18C2)), according to the task. Do you think it might be just wrong?
– Daniel
Nov 19 at 19:12
|
show 2 more comments
So than P(X1=1|X2=1) is equal to probability of intersection of these events divided by p. But isn't the probability of intersection defined as b=1157/(190*153)?
– Daniel
Nov 19 at 12:06
I have made an edit (because finding $P(X_1=2mid X_1=1)$ was a bit more complicated than I thought). Does this help?
– drhab
Nov 19 at 12:41
I still do not understand it completely. I counted this: P(Z=1)=36/190 and P(Z=2)=1/190. P(X2=1∣Z=2)=(2*16+1)/153 But P(X2=1∣Z=1) makes me problem. I think that it is similar to problem above, just there are four cases when the first man picked one his glove and one glove of the second man, so that it is equal to 33-4=29. But then I got in total less than 1157. Could you tell me what is wrong, please?
– Daniel
Nov 19 at 15:57
Again I underestimated the complexity. I edited to provide a way to calculate $P(X_1=X_2=1)$. Do check me on mistakes, though.
– drhab
Nov 19 at 18:16
Thank you very much! I calculated it and I got 1289/((20C2)(18C2)). But it should be 1157/((20C2)(18C2)), according to the task. Do you think it might be just wrong?
– Daniel
Nov 19 at 19:12
So than P(X1=1|X2=1) is equal to probability of intersection of these events divided by p. But isn't the probability of intersection defined as b=1157/(190*153)?
– Daniel
Nov 19 at 12:06
So than P(X1=1|X2=1) is equal to probability of intersection of these events divided by p. But isn't the probability of intersection defined as b=1157/(190*153)?
– Daniel
Nov 19 at 12:06
I have made an edit (because finding $P(X_1=2mid X_1=1)$ was a bit more complicated than I thought). Does this help?
– drhab
Nov 19 at 12:41
I have made an edit (because finding $P(X_1=2mid X_1=1)$ was a bit more complicated than I thought). Does this help?
– drhab
Nov 19 at 12:41
I still do not understand it completely. I counted this: P(Z=1)=36/190 and P(Z=2)=1/190. P(X2=1∣Z=2)=(2*16+1)/153 But P(X2=1∣Z=1) makes me problem. I think that it is similar to problem above, just there are four cases when the first man picked one his glove and one glove of the second man, so that it is equal to 33-4=29. But then I got in total less than 1157. Could you tell me what is wrong, please?
– Daniel
Nov 19 at 15:57
I still do not understand it completely. I counted this: P(Z=1)=36/190 and P(Z=2)=1/190. P(X2=1∣Z=2)=(2*16+1)/153 But P(X2=1∣Z=1) makes me problem. I think that it is similar to problem above, just there are four cases when the first man picked one his glove and one glove of the second man, so that it is equal to 33-4=29. But then I got in total less than 1157. Could you tell me what is wrong, please?
– Daniel
Nov 19 at 15:57
Again I underestimated the complexity. I edited to provide a way to calculate $P(X_1=X_2=1)$. Do check me on mistakes, though.
– drhab
Nov 19 at 18:16
Again I underestimated the complexity. I edited to provide a way to calculate $P(X_1=X_2=1)$. Do check me on mistakes, though.
– drhab
Nov 19 at 18:16
Thank you very much! I calculated it and I got 1289/((20C2)(18C2)). But it should be 1157/((20C2)(18C2)), according to the task. Do you think it might be just wrong?
– Daniel
Nov 19 at 19:12
Thank you very much! I calculated it and I got 1289/((20C2)(18C2)). But it should be 1157/((20C2)(18C2)), according to the task. Do you think it might be just wrong?
– Daniel
Nov 19 at 19:12
|
show 2 more comments
Thanks for contributing an answer to Mathematics Stack Exchange!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
Use MathJax to format equations. MathJax reference.
To learn more, see our tips on writing great answers.
Some of your past answers have not been well-received, and you're in danger of being blocked from answering.
Please pay close attention to the following guidance:
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3004761%2fprobability-expectation-value-and-covariance%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
What's the definition of $b$? The expectation is correct, as it's just linearity. For the variance, consider the formula using the covariance, as it's not clear if the $X_i$ are independent
– Stockfish
Nov 19 at 10:59