zconf {asbio}R Documentation

Z and t confidence intervals for mu.

Description

These functions calculate t and Z confidence intervals for mu. Z confidence intervals require specification of sigma. Both methods assume underlying normal distributions. Finite population corrections are provided if requested.

Usage


zconf(data, conf = 0.95, sigma, summarized = FALSE, xbar = NULL, fpc = FALSE, N = NULL, n = NULL)

tconf(data, conf = 0.95, summarized = FALSE, xbar = NULL, st.dev = NULL, n = NULL, fpc = FALSE, N = NULL)

Arguments

data A vector of quantitative data. Required if summarized = FALSE
conf Confidence level; 1 - alpha.
sigma The population standard deviation.
summarized A logical statement specifying whether statistical summaries are to be used. If summarized = FALSE, then the sample mean and the sample standard deviation (t.conf only) are calculated from the vector provided in data. If summarized = FALSE then the sample mean xbar, the sample size n, and, in the case of t.conf, the sample standard deviation st.dev, must be provided by the user.
xbar The sample mean. Required if summarized = TRUE.
fpc A logical statement specifying whether a finite population correction should be made. If fpc = TRUE then both the sample size n and the population size N must be specified.
N The population size. Required if fpc=TRUE
st.dev The sample standard deviation. Required if summarized=TRUE.
n The sample size. Required if summarized = TRUE.

Details

Z.conf and t.conf calculate confidence intervals for either summarized data or a dataset provided in data. Finite population corrections are made if a user specifies fpc=TRUE and specifies some value for N.

Value

Returns a list

Margin the confidence margin
CI the upper and lower confidence bounds

Author(s)

Ken Aho

References

Lohr, S. L. (1999) Sampling: design and analysis. Duxbury Press. Pacific Grove, USA.

See Also

pnorm, pt

Examples

#With summarized=FALSE 
x<-c(5,10,5,20,30,15,20,25,0,5,10,5,7,10,20,40,30,40,10,5,0,0,3,20,30)
zconf(x,conf=.95,sigma=4,summarized=FALSE)
tconf(x,conf=.95,summarized=FALSE)
#With summarized = TRUE
zconf(x,conf=.95,sigma=4,xbar=14.6,n=25,summarized=TRUE)
tconf(x,conf=.95,st.dev=4,xbar=14.6,n=25,summarized=TRUE)
#with finite population correction and summarized = TRUE
zconf(x,conf=.95,sigma=4,xbar=14.6,n=25,summarized=TRUE,fpc=TRUE,N=100)
tconf(x,conf=.95,st.dev=4,xbar=14.6,n=25,summarized=TRUE,fpc=TRUE,N=100)

[Package asbio version 0.1 Index]