Problems with confidence intervals in R
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Is it possible to use function to create an equation which will produce a normal distribution and simultaneously produce a 95% confidence interval of said data? I know that I can use rnorm(n,mean,sd) to generate a random normal distribution but how do I get the output to tell me the confidence interval?
I have attempted sample_CI<- function(n,j,k){list(g<-rnorm(n, mean=j, sd=k), confint(g, level=.95))}.
All help appreciated.
r normal-distribution confidence-interval
asked Nov 22 at 17:31
Matlab rookie
135
add a comment |
up vote
0
down vote
favorite
Is it possible to use function to create an equation which will produce a normal distribution and simultaneously produce a 95% confidence interval of said data? I know that I can use rnorm(n,mean,sd) to generate a random normal distribution but how do I get the output to tell me the confidence interval?
I have attempted sample_CI<- function(n,j,k){list(g<-rnorm(n, mean=j, sd=k), confint(g, level=.95))}.
All help appreciated.
r normal-distribution confidence-interval
asked Nov 22 at 17:31
Matlab rookie
135
I don't really understand what kind of output you want. Could you give more detail?
– Bram
Nov 22 at 17:45
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
Is it possible to use function to create an equation which will produce a normal distribution and simultaneously produce a 95% confidence interval of said data? I know that I can use rnorm(n,mean,sd) to generate a random normal distribution but how do I get the output to tell me the confidence interval?
I have attempted sample_CI<- function(n,j,k){list(g<-rnorm(n, mean=j, sd=k), confint(g, level=.95))}.
All help appreciated.
r normal-distribution confidence-interval
asked Nov 22 at 17:31
Matlab rookie
135
Is it possible to use function to create an equation which will produce a normal distribution and simultaneously produce a 95% confidence interval of said data? I know that I can use rnorm(n,mean,sd) to generate a random normal distribution but how do I get the output to tell me the confidence interval?
I have attempted sample_CI<- function(n,j,k){list(g<-rnorm(n, mean=j, sd=k), confint(g, level=.95))}.
All help appreciated.
r normal-distribution confidence-interval
r normal-distribution confidence-interval
asked Nov 22 at 17:31
Matlab rookie
135
asked Nov 22 at 17:31
Matlab rookie
135
asked Nov 22 at 17:31
Matlab rookie
135
asked Nov 22 at 17:31
Matlab rookie
135
asked Nov 22 at 17:31
Matlab rookie
135
135
I don't really understand what kind of output you want. Could you give more detail?
– Bram
Nov 22 at 17:45
add a comment |
I don't really understand what kind of output you want. Could you give more detail?
– Bram
Nov 22 at 17:45
I don't really understand what kind of output you want. Could you give more detail?
– Bram
Nov 22 at 17:45
I don't really understand what kind of output you want. Could you give more detail?
– Bram
Nov 22 at 17:45
add a comment |
1 Answer
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0
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It may be this what you were looking for:
sample_CI <- function(n,j,k){
error <- qnorm(0.975)*k/sqrt(n)
left <- j-error
right <- j+error
paste("[",round(left,4)," ; ",round(right,4),"]")
}
sample_CI(1000,2,4)
answered Nov 22 at 17:53
Bram
1298
Whyqnorminstead ofrnorm? Does it make a difference?
– Matlab rookie
Nov 22 at 19:04
@Matlabrookie -qnorm()produces the Z score associated with the area under the curve specified in the first argument to the function. In the case of @Bram's code,qnorm(0.975)= 1.959964, the Z score for the upper bound of the 95% confidence interval. In contrast,rnorm(n)returns n observations randomly drawn from a normal distribution.
– Len Greski
Nov 22 at 20:29
@LenGreski To produce a t score would qnorm also be used?
– Matlab rookie
Nov 22 at 20:41
@Matlabrookie - For Student's t, the quantile function isqt(p,df), whereprepresents the desired probability, anddfrepresents the number of degrees of freedom. Asdfapproaches infinity,qt()approachesqnorm()
– Len Greski
Nov 22 at 20:52
@LenGreski I now want to usereplicate()to produce 1000 different confidence intervals and then check to see how many my mean is contained in. Using theqnormfunction andreplicate()together returns the same confidence interval 1000 times. Should I revert tornorm? and what should I use instead ofqt(p,df)
– Matlab rookie
Nov 22 at 21:31
|
show 1 more comment
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
accepted
It may be this what you were looking for:
sample_CI <- function(n,j,k){
error <- qnorm(0.975)*k/sqrt(n)
left <- j-error
right <- j+error
paste("[",round(left,4)," ; ",round(right,4),"]")
}
sample_CI(1000,2,4)
answered Nov 22 at 17:53
Bram
1298
Whyqnorminstead ofrnorm? Does it make a difference?
– Matlab rookie
Nov 22 at 19:04
@Matlabrookie -qnorm()produces the Z score associated with the area under the curve specified in the first argument to the function. In the case of @Bram's code,qnorm(0.975)= 1.959964, the Z score for the upper bound of the 95% confidence interval. In contrast,rnorm(n)returns n observations randomly drawn from a normal distribution.
– Len Greski
Nov 22 at 20:29
@LenGreski To produce a t score would qnorm also be used?
– Matlab rookie
Nov 22 at 20:41
@Matlabrookie - For Student's t, the quantile function isqt(p,df), whereprepresents the desired probability, anddfrepresents the number of degrees of freedom. Asdfapproaches infinity,qt()approachesqnorm()
– Len Greski
Nov 22 at 20:52
@LenGreski I now want to usereplicate()to produce 1000 different confidence intervals and then check to see how many my mean is contained in. Using theqnormfunction andreplicate()together returns the same confidence interval 1000 times. Should I revert tornorm? and what should I use instead ofqt(p,df)
– Matlab rookie
Nov 22 at 21:31
|
show 1 more comment
up vote
0
down vote
accepted
It may be this what you were looking for:
sample_CI <- function(n,j,k){
error <- qnorm(0.975)*k/sqrt(n)
left <- j-error
right <- j+error
paste("[",round(left,4)," ; ",round(right,4),"]")
}
sample_CI(1000,2,4)
answered Nov 22 at 17:53
Bram
1298
Whyqnorminstead ofrnorm? Does it make a difference?
– Matlab rookie
Nov 22 at 19:04
@Matlabrookie -qnorm()produces the Z score associated with the area under the curve specified in the first argument to the function. In the case of @Bram's code,qnorm(0.975)= 1.959964, the Z score for the upper bound of the 95% confidence interval. In contrast,rnorm(n)returns n observations randomly drawn from a normal distribution.
– Len Greski
Nov 22 at 20:29
@LenGreski To produce a t score would qnorm also be used?
– Matlab rookie
Nov 22 at 20:41
@Matlabrookie - For Student's t, the quantile function isqt(p,df), whereprepresents the desired probability, anddfrepresents the number of degrees of freedom. Asdfapproaches infinity,qt()approachesqnorm()
– Len Greski
Nov 22 at 20:52
@LenGreski I now want to usereplicate()to produce 1000 different confidence intervals and then check to see how many my mean is contained in. Using theqnormfunction andreplicate()together returns the same confidence interval 1000 times. Should I revert tornorm? and what should I use instead ofqt(p,df)
– Matlab rookie
Nov 22 at 21:31
|
show 1 more comment
up vote
0
down vote
accepted
up vote
0
down vote
accepted
It may be this what you were looking for:
sample_CI <- function(n,j,k){
error <- qnorm(0.975)*k/sqrt(n)
left <- j-error
right <- j+error
paste("[",round(left,4)," ; ",round(right,4),"]")
}
sample_CI(1000,2,4)
answered Nov 22 at 17:53
Bram
1298
It may be this what you were looking for:
sample_CI <- function(n,j,k){
error <- qnorm(0.975)*k/sqrt(n)
left <- j-error
right <- j+error
paste("[",round(left,4)," ; ",round(right,4),"]")
}
sample_CI(1000,2,4)
answered Nov 22 at 17:53
Bram
1298
answered Nov 22 at 17:53
Bram
1298
answered Nov 22 at 17:53
Bram
1298
answered Nov 22 at 17:53
Bram
1298
1298
Whyqnorminstead ofrnorm? Does it make a difference?
– Matlab rookie
Nov 22 at 19:04
@Matlabrookie -qnorm()produces the Z score associated with the area under the curve specified in the first argument to the function. In the case of @Bram's code,qnorm(0.975)= 1.959964, the Z score for the upper bound of the 95% confidence interval. In contrast,rnorm(n)returns n observations randomly drawn from a normal distribution.
– Len Greski
Nov 22 at 20:29
@LenGreski To produce a t score would qnorm also be used?
– Matlab rookie
Nov 22 at 20:41
@Matlabrookie - For Student's t, the quantile function isqt(p,df), whereprepresents the desired probability, anddfrepresents the number of degrees of freedom. Asdfapproaches infinity,qt()approachesqnorm()
– Len Greski
Nov 22 at 20:52
@LenGreski I now want to usereplicate()to produce 1000 different confidence intervals and then check to see how many my mean is contained in. Using theqnormfunction andreplicate()together returns the same confidence interval 1000 times. Should I revert tornorm? and what should I use instead ofqt(p,df)
– Matlab rookie
Nov 22 at 21:31
|
show 1 more comment
Whyqnorminstead ofrnorm? Does it make a difference?
– Matlab rookie
Nov 22 at 19:04
@Matlabrookie -qnorm()produces the Z score associated with the area under the curve specified in the first argument to the function. In the case of @Bram's code,qnorm(0.975)= 1.959964, the Z score for the upper bound of the 95% confidence interval. In contrast,rnorm(n)returns n observations randomly drawn from a normal distribution.
– Len Greski
Nov 22 at 20:29
@LenGreski To produce a t score would qnorm also be used?
– Matlab rookie
Nov 22 at 20:41
@Matlabrookie - For Student's t, the quantile function isqt(p,df), whereprepresents the desired probability, anddfrepresents the number of degrees of freedom. Asdfapproaches infinity,qt()approachesqnorm()
– Len Greski
Nov 22 at 20:52
@LenGreski I now want to usereplicate()to produce 1000 different confidence intervals and then check to see how many my mean is contained in. Using theqnormfunction andreplicate()together returns the same confidence interval 1000 times. Should I revert tornorm? and what should I use instead ofqt(p,df)
– Matlab rookie
Nov 22 at 21:31
Why
qnorm instead of rnorm? Does it make a difference?– Matlab rookie
Nov 22 at 19:04
Why
qnorm instead of rnorm? Does it make a difference?– Matlab rookie
Nov 22 at 19:04
@Matlabrookie -
qnorm() produces the Z score associated with the area under the curve specified in the first argument to the function. In the case of @Bram's code, qnorm(0.975) = 1.959964, the Z score for the upper bound of the 95% confidence interval. In contrast, rnorm(n) returns n observations randomly drawn from a normal distribution.– Len Greski
Nov 22 at 20:29
@Matlabrookie -
qnorm() produces the Z score associated with the area under the curve specified in the first argument to the function. In the case of @Bram's code, qnorm(0.975) = 1.959964, the Z score for the upper bound of the 95% confidence interval. In contrast, rnorm(n) returns n observations randomly drawn from a normal distribution.– Len Greski
Nov 22 at 20:29
@LenGreski To produce a t score would qnorm also be used?
– Matlab rookie
Nov 22 at 20:41
@LenGreski To produce a t score would qnorm also be used?
– Matlab rookie
Nov 22 at 20:41
@Matlabrookie - For Student's t, the quantile function is
qt(p,df), where p represents the desired probability, and df represents the number of degrees of freedom. As df approaches infinity, qt() approaches qnorm()– Len Greski
Nov 22 at 20:52
@Matlabrookie - For Student's t, the quantile function is
qt(p,df), where p represents the desired probability, and df represents the number of degrees of freedom. As df approaches infinity, qt() approaches qnorm()– Len Greski
Nov 22 at 20:52
@LenGreski I now want to use
replicate() to produce 1000 different confidence intervals and then check to see how many my mean is contained in. Using the qnorm function and replicate() together returns the same confidence interval 1000 times. Should I revert to rnorm? and what should I use instead of qt(p,df)– Matlab rookie
Nov 22 at 21:31
@LenGreski I now want to use
replicate() to produce 1000 different confidence intervals and then check to see how many my mean is contained in. Using the qnorm function and replicate() together returns the same confidence interval 1000 times. Should I revert to rnorm? and what should I use instead of qt(p,df)– Matlab rookie
Nov 22 at 21:31
|
show 1 more comment
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I don't really understand what kind of output you want. Could you give more detail?
– Bram
Nov 22 at 17:45