How to find sampling distribution of sample mean
$begingroup$
So suppose $Y$ takes values $0$ and $1$ with probabilities
$Pr(Y=1)=p=0.78$ and $Pr(Y=0)=1-p=0.22$
I calculated the mean of Y, which is $0.78$ and the variance of Y, which is $0.1716$.
I also know that the sampling distribution of the sample mean depends on n. For example, let $n=2$, and I want to calculate the sampling distribution of the sample mean .
$overline Y$=sample mean
On the answers sheet, it states that the sampling distribution of the sample mean is :
$Pr(overline Y=0)=(1-p)^2=0.22^2=0.0484$
$Pr(overline Y=0.5)=2·p(1-p)=2·0.22·0.78=0.3432$
$Pr(overline Y=1)=p^2=0.78^2=0.6084$
Now I have two questions:
1) where is the $overline Y=0, overline Y=0.5,overline Y=1$ coming from ? Meaning, where are the $0,0.5,1$ coming from?
2) Once I know the $0,0.5,1$, how to i calculate the sampling distributions? (meaning, where are the $(1-p)^2,2·p(1-p),p^2$ coming from ?)
Thanks for the help, I would greatly appreciate simple and clear answers!
statistics probability-distributions sampling
$endgroup$
add a comment |
$begingroup$
So suppose $Y$ takes values $0$ and $1$ with probabilities
$Pr(Y=1)=p=0.78$ and $Pr(Y=0)=1-p=0.22$
I calculated the mean of Y, which is $0.78$ and the variance of Y, which is $0.1716$.
I also know that the sampling distribution of the sample mean depends on n. For example, let $n=2$, and I want to calculate the sampling distribution of the sample mean .
$overline Y$=sample mean
On the answers sheet, it states that the sampling distribution of the sample mean is :
$Pr(overline Y=0)=(1-p)^2=0.22^2=0.0484$
$Pr(overline Y=0.5)=2·p(1-p)=2·0.22·0.78=0.3432$
$Pr(overline Y=1)=p^2=0.78^2=0.6084$
Now I have two questions:
1) where is the $overline Y=0, overline Y=0.5,overline Y=1$ coming from ? Meaning, where are the $0,0.5,1$ coming from?
2) Once I know the $0,0.5,1$, how to i calculate the sampling distributions? (meaning, where are the $(1-p)^2,2·p(1-p),p^2$ coming from ?)
Thanks for the help, I would greatly appreciate simple and clear answers!
statistics probability-distributions sampling
$endgroup$
add a comment |
$begingroup$
So suppose $Y$ takes values $0$ and $1$ with probabilities
$Pr(Y=1)=p=0.78$ and $Pr(Y=0)=1-p=0.22$
I calculated the mean of Y, which is $0.78$ and the variance of Y, which is $0.1716$.
I also know that the sampling distribution of the sample mean depends on n. For example, let $n=2$, and I want to calculate the sampling distribution of the sample mean .
$overline Y$=sample mean
On the answers sheet, it states that the sampling distribution of the sample mean is :
$Pr(overline Y=0)=(1-p)^2=0.22^2=0.0484$
$Pr(overline Y=0.5)=2·p(1-p)=2·0.22·0.78=0.3432$
$Pr(overline Y=1)=p^2=0.78^2=0.6084$
Now I have two questions:
1) where is the $overline Y=0, overline Y=0.5,overline Y=1$ coming from ? Meaning, where are the $0,0.5,1$ coming from?
2) Once I know the $0,0.5,1$, how to i calculate the sampling distributions? (meaning, where are the $(1-p)^2,2·p(1-p),p^2$ coming from ?)
Thanks for the help, I would greatly appreciate simple and clear answers!
statistics probability-distributions sampling
$endgroup$
So suppose $Y$ takes values $0$ and $1$ with probabilities
$Pr(Y=1)=p=0.78$ and $Pr(Y=0)=1-p=0.22$
I calculated the mean of Y, which is $0.78$ and the variance of Y, which is $0.1716$.
I also know that the sampling distribution of the sample mean depends on n. For example, let $n=2$, and I want to calculate the sampling distribution of the sample mean .
$overline Y$=sample mean
On the answers sheet, it states that the sampling distribution of the sample mean is :
$Pr(overline Y=0)=(1-p)^2=0.22^2=0.0484$
$Pr(overline Y=0.5)=2·p(1-p)=2·0.22·0.78=0.3432$
$Pr(overline Y=1)=p^2=0.78^2=0.6084$
Now I have two questions:
1) where is the $overline Y=0, overline Y=0.5,overline Y=1$ coming from ? Meaning, where are the $0,0.5,1$ coming from?
2) Once I know the $0,0.5,1$, how to i calculate the sampling distributions? (meaning, where are the $(1-p)^2,2·p(1-p),p^2$ coming from ?)
Thanks for the help, I would greatly appreciate simple and clear answers!
statistics probability-distributions sampling
statistics probability-distributions sampling
edited Dec 29 '18 at 17:58
callculus
18.9k31729
18.9k31729
asked Dec 29 '18 at 17:36
BM97BM97
778
778
add a comment |
add a comment |
1 Answer
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$begingroup$
You have two (Bernoulli) independent random variables $Y_1$ and $Y_2$ (with probability of success $p=0.78$) and you want to compute the distribution of the sample mean $overline{Y} := frac{Y_1+Y_2}{2}$.
1) Since the variables $Y_1$ and $Y_2$ can take only the values $0$ and $1$, it is clear that the sample mean can take only the values $0$ (when $Y_1 = Y_2 = 0$), $1$ (when $Y_1 = Y_2 = 1$) or $1/2$ (when $Y_1=0$, $Y_2 = 1$ or viceversa).
2) $P(overline{Y} = 0) = P(Y_1 =0 text{and} Y_2=0) = P(Y_1=0)cdot P(Y_2=0) = (1-p)^2$ (since $Y_1$ and $Y_2$ are independent). Similarly $P(overline{Y} = 1) = p^2$.
Finally,
$$
P(overline{Y} = 1/2) = P(Y_1 =0 text{and} Y_2=1) + P(Y_1 =1 text{and} Y_2=0) =
2p(1-p).
$$
$endgroup$
$begingroup$
Thankyou!!!!! You are awesome. Greatly appreciated-
$endgroup$
– BM97
Dec 29 '18 at 17:51
add a comment |
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$begingroup$
You have two (Bernoulli) independent random variables $Y_1$ and $Y_2$ (with probability of success $p=0.78$) and you want to compute the distribution of the sample mean $overline{Y} := frac{Y_1+Y_2}{2}$.
1) Since the variables $Y_1$ and $Y_2$ can take only the values $0$ and $1$, it is clear that the sample mean can take only the values $0$ (when $Y_1 = Y_2 = 0$), $1$ (when $Y_1 = Y_2 = 1$) or $1/2$ (when $Y_1=0$, $Y_2 = 1$ or viceversa).
2) $P(overline{Y} = 0) = P(Y_1 =0 text{and} Y_2=0) = P(Y_1=0)cdot P(Y_2=0) = (1-p)^2$ (since $Y_1$ and $Y_2$ are independent). Similarly $P(overline{Y} = 1) = p^2$.
Finally,
$$
P(overline{Y} = 1/2) = P(Y_1 =0 text{and} Y_2=1) + P(Y_1 =1 text{and} Y_2=0) =
2p(1-p).
$$
$endgroup$
$begingroup$
Thankyou!!!!! You are awesome. Greatly appreciated-
$endgroup$
– BM97
Dec 29 '18 at 17:51
add a comment |
$begingroup$
You have two (Bernoulli) independent random variables $Y_1$ and $Y_2$ (with probability of success $p=0.78$) and you want to compute the distribution of the sample mean $overline{Y} := frac{Y_1+Y_2}{2}$.
1) Since the variables $Y_1$ and $Y_2$ can take only the values $0$ and $1$, it is clear that the sample mean can take only the values $0$ (when $Y_1 = Y_2 = 0$), $1$ (when $Y_1 = Y_2 = 1$) or $1/2$ (when $Y_1=0$, $Y_2 = 1$ or viceversa).
2) $P(overline{Y} = 0) = P(Y_1 =0 text{and} Y_2=0) = P(Y_1=0)cdot P(Y_2=0) = (1-p)^2$ (since $Y_1$ and $Y_2$ are independent). Similarly $P(overline{Y} = 1) = p^2$.
Finally,
$$
P(overline{Y} = 1/2) = P(Y_1 =0 text{and} Y_2=1) + P(Y_1 =1 text{and} Y_2=0) =
2p(1-p).
$$
$endgroup$
$begingroup$
Thankyou!!!!! You are awesome. Greatly appreciated-
$endgroup$
– BM97
Dec 29 '18 at 17:51
add a comment |
$begingroup$
You have two (Bernoulli) independent random variables $Y_1$ and $Y_2$ (with probability of success $p=0.78$) and you want to compute the distribution of the sample mean $overline{Y} := frac{Y_1+Y_2}{2}$.
1) Since the variables $Y_1$ and $Y_2$ can take only the values $0$ and $1$, it is clear that the sample mean can take only the values $0$ (when $Y_1 = Y_2 = 0$), $1$ (when $Y_1 = Y_2 = 1$) or $1/2$ (when $Y_1=0$, $Y_2 = 1$ or viceversa).
2) $P(overline{Y} = 0) = P(Y_1 =0 text{and} Y_2=0) = P(Y_1=0)cdot P(Y_2=0) = (1-p)^2$ (since $Y_1$ and $Y_2$ are independent). Similarly $P(overline{Y} = 1) = p^2$.
Finally,
$$
P(overline{Y} = 1/2) = P(Y_1 =0 text{and} Y_2=1) + P(Y_1 =1 text{and} Y_2=0) =
2p(1-p).
$$
$endgroup$
You have two (Bernoulli) independent random variables $Y_1$ and $Y_2$ (with probability of success $p=0.78$) and you want to compute the distribution of the sample mean $overline{Y} := frac{Y_1+Y_2}{2}$.
1) Since the variables $Y_1$ and $Y_2$ can take only the values $0$ and $1$, it is clear that the sample mean can take only the values $0$ (when $Y_1 = Y_2 = 0$), $1$ (when $Y_1 = Y_2 = 1$) or $1/2$ (when $Y_1=0$, $Y_2 = 1$ or viceversa).
2) $P(overline{Y} = 0) = P(Y_1 =0 text{and} Y_2=0) = P(Y_1=0)cdot P(Y_2=0) = (1-p)^2$ (since $Y_1$ and $Y_2$ are independent). Similarly $P(overline{Y} = 1) = p^2$.
Finally,
$$
P(overline{Y} = 1/2) = P(Y_1 =0 text{and} Y_2=1) + P(Y_1 =1 text{and} Y_2=0) =
2p(1-p).
$$
answered Dec 29 '18 at 17:46
RigelRigel
11.4k11320
11.4k11320
$begingroup$
Thankyou!!!!! You are awesome. Greatly appreciated-
$endgroup$
– BM97
Dec 29 '18 at 17:51
add a comment |
$begingroup$
Thankyou!!!!! You are awesome. Greatly appreciated-
$endgroup$
– BM97
Dec 29 '18 at 17:51
$begingroup$
Thankyou!!!!! You are awesome. Greatly appreciated-
$endgroup$
– BM97
Dec 29 '18 at 17:51
$begingroup$
Thankyou!!!!! You are awesome. Greatly appreciated-
$endgroup$
– BM97
Dec 29 '18 at 17:51
add a comment |
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