Statistics and Confidence IntervalsConstruct a Confidence Interval of $95%$Confidence level of random sample from continuous distributionConfidence interval - No sampleInterval estimate to infer the population mean with a 95% confidence levelConfidence IntervalsConfidence Intervals Calculation and InterpretationConfidence intervals and significance testsHow to determine a confidence interval without knowing mean and varianceReducing the confidence interval with T distribitionConfidence Intervals using Pivotal Quantities
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Statistics and Confidence Intervals
Construct a Confidence Interval of $95%$Confidence level of random sample from continuous distributionConfidence interval - No sampleInterval estimate to infer the population mean with a 95% confidence levelConfidence IntervalsConfidence Intervals Calculation and InterpretationConfidence intervals and significance testsHow to determine a confidence interval without knowing mean and varianceReducing the confidence interval with T distribitionConfidence Intervals using Pivotal Quantities
$begingroup$
Given the following set of values:
10,11,14,95,73,30,29,9,97,94,70
How do I calculate a 99% confidence interval for the sample mean? I am assuming that the variance is 10
Well, the idea I have is to assume that the distribution is normal, but after that i'm not completely sure what to do next. In particular, I am unable to find the z-score that corresponds to the z-score in the formula for the CI, i'm not sure what to input in R to find the CI. The formula for the confidence interval is:
$x-z_fraca2 fracsigma^2sqrt(n)$ and $x+z_fraca2 fracsigma^2sqrt(n)$ where x denotes the mean. Here the significance level (a) is 0.01.
statistics probability-distributions normal-distribution statistical-inference
$endgroup$
add a comment |
$begingroup$
Given the following set of values:
10,11,14,95,73,30,29,9,97,94,70
How do I calculate a 99% confidence interval for the sample mean? I am assuming that the variance is 10
Well, the idea I have is to assume that the distribution is normal, but after that i'm not completely sure what to do next. In particular, I am unable to find the z-score that corresponds to the z-score in the formula for the CI, i'm not sure what to input in R to find the CI. The formula for the confidence interval is:
$x-z_fraca2 fracsigma^2sqrt(n)$ and $x+z_fraca2 fracsigma^2sqrt(n)$ where x denotes the mean. Here the significance level (a) is 0.01.
statistics probability-distributions normal-distribution statistical-inference
$endgroup$
$begingroup$
What are your thoughts? Are you familiar with any formulas that concern confidence intervals? What computations can you do?
$endgroup$
– Brian
Mar 21 at 17:56
$begingroup$
Well, I know the formula for the confidence interval, but i'm not sure how to find the z-score, I know that I can use R, but i'm not sure what to write in R.
$endgroup$
– topologicalmagician
Mar 21 at 17:57
$begingroup$
Do you know what the "99%" in the confidence interval means? Can you relate this to the Normal distribution in some way? Do you know how z-scores relate to the Normal distribution?
$endgroup$
– Brian
Mar 21 at 18:00
$begingroup$
@Brian Yes, a CI is the 100(1-a)% interval in which the true parameter lies in, a is the significance level. The formula for the CI is : $x+z_fraca2 fracsigma^2sqrt(n)$ and : $x-z_fraca2 fracsigma^2sqrt(n)$ where x denotes the mean
$endgroup$
– topologicalmagician
Mar 21 at 18:04
add a comment |
$begingroup$
Given the following set of values:
10,11,14,95,73,30,29,9,97,94,70
How do I calculate a 99% confidence interval for the sample mean? I am assuming that the variance is 10
Well, the idea I have is to assume that the distribution is normal, but after that i'm not completely sure what to do next. In particular, I am unable to find the z-score that corresponds to the z-score in the formula for the CI, i'm not sure what to input in R to find the CI. The formula for the confidence interval is:
$x-z_fraca2 fracsigma^2sqrt(n)$ and $x+z_fraca2 fracsigma^2sqrt(n)$ where x denotes the mean. Here the significance level (a) is 0.01.
statistics probability-distributions normal-distribution statistical-inference
$endgroup$
Given the following set of values:
10,11,14,95,73,30,29,9,97,94,70
How do I calculate a 99% confidence interval for the sample mean? I am assuming that the variance is 10
Well, the idea I have is to assume that the distribution is normal, but after that i'm not completely sure what to do next. In particular, I am unable to find the z-score that corresponds to the z-score in the formula for the CI, i'm not sure what to input in R to find the CI. The formula for the confidence interval is:
$x-z_fraca2 fracsigma^2sqrt(n)$ and $x+z_fraca2 fracsigma^2sqrt(n)$ where x denotes the mean. Here the significance level (a) is 0.01.
statistics probability-distributions normal-distribution statistical-inference
statistics probability-distributions normal-distribution statistical-inference
edited Mar 21 at 18:11
topologicalmagician
asked Mar 21 at 17:50
topologicalmagiciantopologicalmagician
1199
1199
$begingroup$
What are your thoughts? Are you familiar with any formulas that concern confidence intervals? What computations can you do?
$endgroup$
– Brian
Mar 21 at 17:56
$begingroup$
Well, I know the formula for the confidence interval, but i'm not sure how to find the z-score, I know that I can use R, but i'm not sure what to write in R.
$endgroup$
– topologicalmagician
Mar 21 at 17:57
$begingroup$
Do you know what the "99%" in the confidence interval means? Can you relate this to the Normal distribution in some way? Do you know how z-scores relate to the Normal distribution?
$endgroup$
– Brian
Mar 21 at 18:00
$begingroup$
@Brian Yes, a CI is the 100(1-a)% interval in which the true parameter lies in, a is the significance level. The formula for the CI is : $x+z_fraca2 fracsigma^2sqrt(n)$ and : $x-z_fraca2 fracsigma^2sqrt(n)$ where x denotes the mean
$endgroup$
– topologicalmagician
Mar 21 at 18:04
add a comment |
$begingroup$
What are your thoughts? Are you familiar with any formulas that concern confidence intervals? What computations can you do?
$endgroup$
– Brian
Mar 21 at 17:56
$begingroup$
Well, I know the formula for the confidence interval, but i'm not sure how to find the z-score, I know that I can use R, but i'm not sure what to write in R.
$endgroup$
– topologicalmagician
Mar 21 at 17:57
$begingroup$
Do you know what the "99%" in the confidence interval means? Can you relate this to the Normal distribution in some way? Do you know how z-scores relate to the Normal distribution?
$endgroup$
– Brian
Mar 21 at 18:00
$begingroup$
@Brian Yes, a CI is the 100(1-a)% interval in which the true parameter lies in, a is the significance level. The formula for the CI is : $x+z_fraca2 fracsigma^2sqrt(n)$ and : $x-z_fraca2 fracsigma^2sqrt(n)$ where x denotes the mean
$endgroup$
– topologicalmagician
Mar 21 at 18:04
$begingroup$
What are your thoughts? Are you familiar with any formulas that concern confidence intervals? What computations can you do?
$endgroup$
– Brian
Mar 21 at 17:56
$begingroup$
What are your thoughts? Are you familiar with any formulas that concern confidence intervals? What computations can you do?
$endgroup$
– Brian
Mar 21 at 17:56
$begingroup$
Well, I know the formula for the confidence interval, but i'm not sure how to find the z-score, I know that I can use R, but i'm not sure what to write in R.
$endgroup$
– topologicalmagician
Mar 21 at 17:57
$begingroup$
Well, I know the formula for the confidence interval, but i'm not sure how to find the z-score, I know that I can use R, but i'm not sure what to write in R.
$endgroup$
– topologicalmagician
Mar 21 at 17:57
$begingroup$
Do you know what the "99%" in the confidence interval means? Can you relate this to the Normal distribution in some way? Do you know how z-scores relate to the Normal distribution?
$endgroup$
– Brian
Mar 21 at 18:00
$begingroup$
Do you know what the "99%" in the confidence interval means? Can you relate this to the Normal distribution in some way? Do you know how z-scores relate to the Normal distribution?
$endgroup$
– Brian
Mar 21 at 18:00
$begingroup$
@Brian Yes, a CI is the 100(1-a)% interval in which the true parameter lies in, a is the significance level. The formula for the CI is : $x+z_fraca2 fracsigma^2sqrt(n)$ and : $x-z_fraca2 fracsigma^2sqrt(n)$ where x denotes the mean
$endgroup$
– topologicalmagician
Mar 21 at 18:04
$begingroup$
@Brian Yes, a CI is the 100(1-a)% interval in which the true parameter lies in, a is the significance level. The formula for the CI is : $x+z_fraca2 fracsigma^2sqrt(n)$ and : $x-z_fraca2 fracsigma^2sqrt(n)$ where x denotes the mean
$endgroup$
– topologicalmagician
Mar 21 at 18:04
add a comment |
1 Answer
1
active
oldest
votes
$begingroup$
It is likely that you are asked to find a confidence interval for the (unknown) population mean, not the sample mean. The sample mean is not a parameter of interest, it can be calculated from the sample.
A conventional setup for the problem is that you have a sample $mathbf X=(X_1,X_2,ldots,X_n)$ of size $n=11$ from a $N(mu,sigma_0^2)$ population (by assumption) with $sigma_0^2=10$. You have to find a confidence interval for the mean $mu$.
A suitable pivotal quantity here is $$Q(mathbf X,mu)=fracsqrtn(overline X-mu)sigma_0sim N(0,1)$$
, where $overline X=frac1nsumlimits_i=1^n X_i$ is the sample mean.
So if $z_alpha/2$ be such that $P(Z>z_alpha/2)=alpha/2$ where $Zsim N(0,1)$, you have $$P_mu(-z_alpha/2le Qle z_alpha/2)=1-alphaquad,forall,mu$$
You have to use the above to arrive at the form $$P_mu(c_1,le mule,, c_2)=1-alphaquad,forall,mu$$
A $100(1-alpha)%$ confidence interval for $mu$ is then $[c_1,c_2]$.
$endgroup$
add a comment |
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1 Answer
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1 Answer
1
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oldest
votes
$begingroup$
It is likely that you are asked to find a confidence interval for the (unknown) population mean, not the sample mean. The sample mean is not a parameter of interest, it can be calculated from the sample.
A conventional setup for the problem is that you have a sample $mathbf X=(X_1,X_2,ldots,X_n)$ of size $n=11$ from a $N(mu,sigma_0^2)$ population (by assumption) with $sigma_0^2=10$. You have to find a confidence interval for the mean $mu$.
A suitable pivotal quantity here is $$Q(mathbf X,mu)=fracsqrtn(overline X-mu)sigma_0sim N(0,1)$$
, where $overline X=frac1nsumlimits_i=1^n X_i$ is the sample mean.
So if $z_alpha/2$ be such that $P(Z>z_alpha/2)=alpha/2$ where $Zsim N(0,1)$, you have $$P_mu(-z_alpha/2le Qle z_alpha/2)=1-alphaquad,forall,mu$$
You have to use the above to arrive at the form $$P_mu(c_1,le mule,, c_2)=1-alphaquad,forall,mu$$
A $100(1-alpha)%$ confidence interval for $mu$ is then $[c_1,c_2]$.
$endgroup$
add a comment |
$begingroup$
It is likely that you are asked to find a confidence interval for the (unknown) population mean, not the sample mean. The sample mean is not a parameter of interest, it can be calculated from the sample.
A conventional setup for the problem is that you have a sample $mathbf X=(X_1,X_2,ldots,X_n)$ of size $n=11$ from a $N(mu,sigma_0^2)$ population (by assumption) with $sigma_0^2=10$. You have to find a confidence interval for the mean $mu$.
A suitable pivotal quantity here is $$Q(mathbf X,mu)=fracsqrtn(overline X-mu)sigma_0sim N(0,1)$$
, where $overline X=frac1nsumlimits_i=1^n X_i$ is the sample mean.
So if $z_alpha/2$ be such that $P(Z>z_alpha/2)=alpha/2$ where $Zsim N(0,1)$, you have $$P_mu(-z_alpha/2le Qle z_alpha/2)=1-alphaquad,forall,mu$$
You have to use the above to arrive at the form $$P_mu(c_1,le mule,, c_2)=1-alphaquad,forall,mu$$
A $100(1-alpha)%$ confidence interval for $mu$ is then $[c_1,c_2]$.
$endgroup$
add a comment |
$begingroup$
It is likely that you are asked to find a confidence interval for the (unknown) population mean, not the sample mean. The sample mean is not a parameter of interest, it can be calculated from the sample.
A conventional setup for the problem is that you have a sample $mathbf X=(X_1,X_2,ldots,X_n)$ of size $n=11$ from a $N(mu,sigma_0^2)$ population (by assumption) with $sigma_0^2=10$. You have to find a confidence interval for the mean $mu$.
A suitable pivotal quantity here is $$Q(mathbf X,mu)=fracsqrtn(overline X-mu)sigma_0sim N(0,1)$$
, where $overline X=frac1nsumlimits_i=1^n X_i$ is the sample mean.
So if $z_alpha/2$ be such that $P(Z>z_alpha/2)=alpha/2$ where $Zsim N(0,1)$, you have $$P_mu(-z_alpha/2le Qle z_alpha/2)=1-alphaquad,forall,mu$$
You have to use the above to arrive at the form $$P_mu(c_1,le mule,, c_2)=1-alphaquad,forall,mu$$
A $100(1-alpha)%$ confidence interval for $mu$ is then $[c_1,c_2]$.
$endgroup$
It is likely that you are asked to find a confidence interval for the (unknown) population mean, not the sample mean. The sample mean is not a parameter of interest, it can be calculated from the sample.
A conventional setup for the problem is that you have a sample $mathbf X=(X_1,X_2,ldots,X_n)$ of size $n=11$ from a $N(mu,sigma_0^2)$ population (by assumption) with $sigma_0^2=10$. You have to find a confidence interval for the mean $mu$.
A suitable pivotal quantity here is $$Q(mathbf X,mu)=fracsqrtn(overline X-mu)sigma_0sim N(0,1)$$
, where $overline X=frac1nsumlimits_i=1^n X_i$ is the sample mean.
So if $z_alpha/2$ be such that $P(Z>z_alpha/2)=alpha/2$ where $Zsim N(0,1)$, you have $$P_mu(-z_alpha/2le Qle z_alpha/2)=1-alphaquad,forall,mu$$
You have to use the above to arrive at the form $$P_mu(c_1,le mule,, c_2)=1-alphaquad,forall,mu$$
A $100(1-alpha)%$ confidence interval for $mu$ is then $[c_1,c_2]$.
edited Mar 21 at 19:07
answered Mar 21 at 18:56
StubbornAtomStubbornAtom
6,29831440
6,29831440
add a comment |
add a comment |
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$begingroup$
What are your thoughts? Are you familiar with any formulas that concern confidence intervals? What computations can you do?
$endgroup$
– Brian
Mar 21 at 17:56
$begingroup$
Well, I know the formula for the confidence interval, but i'm not sure how to find the z-score, I know that I can use R, but i'm not sure what to write in R.
$endgroup$
– topologicalmagician
Mar 21 at 17:57
$begingroup$
Do you know what the "99%" in the confidence interval means? Can you relate this to the Normal distribution in some way? Do you know how z-scores relate to the Normal distribution?
$endgroup$
– Brian
Mar 21 at 18:00
$begingroup$
@Brian Yes, a CI is the 100(1-a)% interval in which the true parameter lies in, a is the significance level. The formula for the CI is : $x+z_fraca2 fracsigma^2sqrt(n)$ and : $x-z_fraca2 fracsigma^2sqrt(n)$ where x denotes the mean
$endgroup$
– topologicalmagician
Mar 21 at 18:04