numSummary

From Rcmdr v2.0-4 by John Fox

Summary Statistics for Numeric Variables

numSummary creates neatly formatted tables of means, standard deviations, coefficients of variation, skewness, kurtosis, and quantiles of numeric variables.

Keywords: misc

Usage

numSummary(data, 
	statistics=c("mean", "sd", "IQR", "quantiles", "cv", "skewness", "kurtosis"),
	type=c("2", "1", "3"),
    quantiles=c(0, .25, .5, .75, 1), groups)
    
## S3 method for class 'numSummary':
print(x, ...)

Arguments

data: a numeric vector, matrix, or data frame.
statistics: any of "mean", "sd", "quantiles", "cv" (coefficient of variation --- sd/mean), "skewness", or "kurtosis", defaulting to the first three.
type: definition to use in computing skewness and kurtosis; see the skewness and kurtosis functions in the e1071 package. The defau
quantiles: quantiles to report; default is c(0, 0.25, 0.5, 0.75, 1).
groups: optional variable, typically a factor, to be used to partition the data.
x: object of class "numSummary" to print.
...: arguments to pass down from the print method.

Value

numSummary returns an object of class "numSummary" containing the table of statistics to be reported along with information on missing data, if there are any.

Examples

data(Prestige, package="car")
Prestige[1, "income"] <- NA
numSummary(Prestige[,c("income", "education")], 
	statistics=c("mean", "sd", "quantiles", "cv", "skewness", "kurtosis"))
numSummary(Prestige[,c("income", "education")], groups=Prestige$type)
remove(Prestige)

Documentation reproduced from package Rcmdr, version 2.0-4, License: GPL (>= 2)

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