SixSigma (version 0.9-2)

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"))

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

Value

• The confidence Interval. A graph with the figures, the Shapiro-Wilks test, and a histogram.

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. http://www.springer.com/statistics/book/978-1-4614-3651-5.

See Also

ss.data.rr

Examples

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