SixSigma (version 0.11.1)

ss.ci: Confidence Interval for the mean

Description

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.

Usage

ss.ci(
  x,
  sigma2 = NA,
  alpha = 0.05,
  data = NA,
  xname = "x",
  approx.z = FALSE,
  main = "Confidence Interval for the Mean",
  digits = 3,
  sub = "",
  ss.col = c("#666666", "#BBBBBB", "#CCCCCC", "#DDDDDD", "#EEEEEE", "#FFFFFF", "#000000",
    "#000000")
)

Value

The confidence Interval.

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

Arguments

x

A numeric vector with the variable data

sigma2

The population variance, if known

alpha

The eqn\alpha error used to compute the \(100*(1-\\alpha)\%\) confidence interval

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

Author

EL Cano

Details

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.

References

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. https://link.springer.com/book/10.1007/978-1-4614-3652-2.

See Also

ss.data.rr

Examples

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