Rcmdr (version 2.0-1)

numSummary: Summary Statistics for Numeric Variables

Description

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

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.

See Also

mean, sd, quantile, skewness, kurtosis.

Examples

Run this code
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)

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