asbio (version 1.12-1)

ci.mu.z: Z and t confidence intervals for mu.

Description

These functions calculate t and z confidence intervals for \(\mu\). Z confidence intervals require specification (and thus knowledge) of \(\sigma\). Both methods assume underlying normal distributions although this assumption becomes irrelevant for large sample sizes. Finite population corrections are provided if requested.

Usage

ci.mu.z(data, conf = 0.95, sigma = 1, summarized = FALSE, xbar = NULL,
fpc = FALSE, N = NULL, n = NULL, na.rm = FALSE)
ci.mu.t(data, conf = 0.95, summarized = FALSE, xbar = NULL, sd = NULL, 
fpc = FALSE, N = NULL, n = NULL, na.rm = FALSE)

Value

Returns a list of class = "ci". Default printed results are the parameter estimate and confidence bounds. Other invisible objects include:

Margin

the confidence margin.

Details

ci.mu.z and ci.mu.t 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 provides some value for N.

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)
ci.mu.z(x,conf=.95,sigma=4,summarized=FALSE)
ci.mu.t(x,conf=.95,summarized=FALSE)
#With summarized = TRUE
ci.mu.z(x,conf=.95,sigma=4,xbar=14.6,n=25,summarized=TRUE)
ci.mu.t(x,conf=.95,sd=4,xbar=14.6,n=25,summarized=TRUE)
#with finite population correction and summarized = TRUE
ci.mu.z(x,conf=.95,sigma=4,xbar=14.6,n=25,summarized=TRUE,fpc=TRUE,N=100)
ci.mu.t(x,conf=.95,sd=4,xbar=14.6,n=25,summarized=TRUE,fpc=TRUE,N=100)