ci.mu.oneside {asbio} | R Documentation |

## One sided confidence interval for mu.

### Description

In some situations we may wish to quantify confidence in the region above or below a mean estimate. For instance, a biologist working with an endangered species may be interested in saying: "I am 95 percent confident that the true mean number of offspring is above a particular threshold." In a one-sided situation, we essentially let our confidence be 1- 2`\alpha`

(instead of 1 - `\alpha`

).
Thus, if our significance level for a two-tailed test is `\alpha`

, our one-tailed significance level will be 2`\alpha`

.

### Usage

```
ci.mu.oneside(data, conf = 0.95, n = NULL, Var = NULL, xbar = NULL,
summarized = FALSE, N = NULL, fpc = FALSE, tail = "upper", na.rm = FALSE)
```

### Arguments

`data` |
A vector of quantitative data. Required if |

`conf` |
Level of confidence; 1 - |

`n` |
Sample size. Required if |

`Var` |
Sample variance. Required if |

`xbar` |
Sample mean. Required if |

`summarized` |
Logical. Indicates whether summary statistics instead of raw data should be used. |

`N` |
Population size. Required if |

`fpc` |
Logical. Indicating whether finite population corrections should be made. |

`tail` |
Indicates what side the one sided confidence limit should be calculated for. Choices are |

`na.rm` |
Logical, indicate whether |

### Value

Returns a list of `class = "ci"`

. Default output is a matrix with the sample mean and either the upper or lower confidence limit.

### Author(s)

Ken Aho

### References

Bain, L. J., and Engelhardt, M. (1992) *Introduction to Probability and Mathematical
Statistics*. Duxbury press, Belmont, CA, USA.

### See Also

### Examples

```
ci.mu.oneside(rnorm(100))
```

*asbio*version 1.9-7 Index]