The function `sample.size.mean`

returns the sample size needed for mean estimations either with or without consideration of finite population correction.

sample.size.mean(e, S, N = Inf, level = 0.95)

## Arguments

e |
positive number specifying the precision which is half width of confidence interval |

S |
standard deviation in population |

N |
positive integer for population size. Default is `N=Inf` , which means that calculations are carried out without finite population correction. |

level |
coverage probability for confidence intervals. Default is `level=0.95` . |

## Value

The function `sample.size.mean`

returns a value, which is a list consisting of the components

callis a list of call components: `e`

precision, `S`

standard deviation in population, and `N`

integer for population size

nestimate of sample size

## References

Kauermann, Goeran/Kuechenhoff, Helmut (2010): Stichproben. Methoden und praktische Umsetzung mit R. Springer.

## Author

Juliane Manitz

## See also

## Examples

# sample size for precision e=4
sample.size.mean(e=4,S=10,N=300)

#>
#> sample.size.mean object: Sample size for mean estimate
#> With finite population correction: N=300, precision e=4 and standard deviation S=10
#>
#> Sample size needed: 23
#>

# sample size for precision e=1
sample.size.mean(e=1,S=10,N=300)

#>
#> sample.size.mean object: Sample size for mean estimate
#> With finite population correction: N=300, precision e=1 and standard deviation S=10
#>
#> Sample size needed: 169
#>