# ciMean

From lsr v0.5
0th

Percentile

##### Confidence interval around the mean

Calculates confidence intervals for the mean of a normally-distributed variable.

##### Usage
ciMean(x, conf = 0.95, na.rm = FALSE)
##### Arguments
x
A numeric vector, data frame or matrix containing the observations.
conf
The level of confidence desired. Defaults to a 95% confidence interval
na.rm
Logical value indicating whether missing values are to be removed. Defaults to FALSE.
##### Details

This function calculates the confidence interval for the mean of a variable (or set of variables in a data frame or matrix), under the standard assumption that the data are normally distributed. By default it returns a 95% confidence interval (conf = 0.95) and does not remove missing values (na.rm = FALSE).

##### Value

The output is a matrix containing the lower and upper ends of the confidence interval for each variable. If a data frame is specified as input and contains non-numeric variables, the corresponding rows in the output matrix have NA values.

##### Warning

This package is under development, and has been released only due to teaching constraints. Until this notice disappears from the help files, you should assume that everything in the package is subject to change. Backwards compatibility is NOT guaranteed. Functions may be deleted in future versions and new syntax may be inconsistent with earlier versions. For the moment at least, this package should be treated with extreme caution.

confint
library(lsr) X <- c(1, 3, 6) # data ciMean(X) # 95 percent confidence interval ciMean(X, conf = .8) # 80 percent confidence interval confint( lm(X ~ 1) ) # for comparison purposes X <- c(1, 3, NA, 6) # data with missing values ciMean(X, na.rm = TRUE) # remove missing values