Computes a confidence interval for the mean of the variable (parameter or feature of the process), and prints the data, a histogram with a density line, the result of the Shapiro-Wilks normality test and a quantile-quantile plot.

1 2 3 4 |

`x` |
A numeric vector with the variable data |

`sigma2` |
The population variance, if known |

`alpha` |
The eqn\alpha error used to compute the |

`data` |
The data frame containing the vector |

`xname` |
The name of the variable to be shown in the graph |

`approx.z` |
If TRUE it uses z statistic instead of t when sigma is unknown and sample size is greater than 30. The default is FALSE, change only if you want to compare with results obtained with the old-fashioned method mentioned in some books. |

`main` |
The main title for the graph |

`digits` |
Significant digits for output |

`sub` |
The subtitle for the graph (recommended: six sigma project name) |

`ss.col` |
A vector with colors |

When the population variance is known, or the size is greater than 30,
it uses z statistic. Otherwise, it is uses t statistic.

If the sample size is lower than 30, a warning is displayed so as to
verify normality.

The confidence Interval.

A graph with the figures, the Shapiro-Wilks test, and a histogram.

Thanks to the kind comments and suggestions from the anonymous reviewer of a tentative article.

EL Cano

Cano, Emilio L., Moguerza, Javier M. and Redchuk, Andres. 2012.
*Six Sigma with R. Statistical Engineering for Process
Improvement*, Use R!, vol. 36. Springer, New York.
http://www.springer.com/statistics/book/978-1-4614-3651-5.

1 2 3 | ```
ss.ci(len, data=ss.data.strings, alpha = 0.05,
sub = "Guitar Strings Test | String Length",
xname = "Length")
``` |

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