CIsim {BSDA} | R Documentation |

## Confidence Interval Simulation Program

### Description

This program simulates random samples from which it constructs confidence intervals for one of the parameters mean (Mu), variance (Sigma), or proportion of successes (Pi).

### Usage

```
CIsim(
samples = 100,
n = 30,
mu = 0,
sigma = 1,
conf.level = 0.95,
type = "Mean"
)
```

### Arguments

`samples` |
the number of samples desired. |

`n` |
the size of each sample. |

`mu` |
if constructing confidence intervals for the population mean or
the population variance, mu is the population mean (i.e., type is one of
either |

`sigma` |
the population standard deviation. |

`conf.level` |
confidence level for the graphed confidence intervals, restricted to lie between zero and one. |

`type` |
character string, one of |

### Details

Default is to construct confidence intervals for the population mean. Simulated confidence intervals for the population variance or population proportion of successes are possible by selecting the appropriate value in the type argument.

### Value

Graph depicts simulated confidence intervals. The number of confidence intervals that do not contain the parameter of interest are counted and reported in the commands window.

### Author(s)

Alan T. Arnholt

### Examples

```
CIsim(100, 30, 100, 10)
# Simulates 100 samples of size 30 from
# a normal distribution with mean 100
# and standard deviation 10. From the
# 100 simulated samples, 95% confidence
# intervals for the Mean are constructed
# and depicted in the graph.
CIsim(100, 30, 100, 10, type="Var")
# Simulates 100 samples of size 30 from
# a normal distribution with mean 100
# and standard deviation 10. From the
# 100 simulated samples, 95% confidence
# intervals for the variance are constructed
# and depicted in the graph.
CIsim(100, 50, .5, type="Pi", conf.level=.90)
# Simulates 100 samples of size 50 from
# a binomial distribution where the population
# proportion of successes is 0.5. From the
# 100 simulated samples, 90% confidence
# intervals for Pi are constructed
# and depicted in the graph.
```

*BSDA*version 1.2.2 Index]