oii.summary: Print summary statistics for a numeric variable
In oii: Crosstab and Statistical Tests for OII MSc Stats Course

Description Usage Arguments Value See Also Examples

This function is designed to be like the built-in summary function but include a few additional values. If the input is not numeric, the built-in summary command is executed.

1	oii.summary(x, extended = FALSE, warnings = FALSE)

`x`	a numeric vector for which summary statistics should be generated.
`extended`	a logical value indicating whether additional statistics should be printed (see Value section). Defaults to FALSE stripped before the computation proceeds (defaults to TRUE).
`warnings`	a logical value indicating whether warnings should be shown (defaults to FALSE, no warnings).

If x is not numeric, the built-in summary command is executed. If x is numeric (that is, is.numeric(x) returns TRUE), then a list with the following elements is returned:

`cases`	The number of non-missing values in `x` (Valid N)
`na`	The number of missing values in `x` (Missing N).
`mean`	The mean value of `x` after missing values are removed. See `mean`
`sd`	The standard deviation for values in `x`. See `sd`
`min`	The minimum/smallest value in `x`. See `min`
`max`	The maximum/largest value in `x`. See `max`

This function also calculates the following statistics, but these are not printed by default unless extended is set to TRUE

`var`	The variance of `x` after missing values are removed. See `var`
`median`	The median value of `x` after missing values are removed. See `median`
`p25`	The 25th percentile of `x` after missing values are removed
`p75`	The 75th percentile of `x` after missing values are removed
`skewness`	The skewness coefficient for `x` after missing values are removed. See `skewness`
`kurtosis`	The kurtosis coefficient for `x` after missing values are removed. See `kurtosis`

summary, min, median, mean, max, sd, is.na, is.numeric, skewness, kurtosis, var

#Generate data from a normal distribution with mean 0 and sd 1
#store the result in a variable called tmp
tmp<-rnorm(500,mean=0,sd=1)

#Print the summary statistics about tmp
oii.summary(tmp)
#Print even more summary statistics about tmp
oii.summary(tmp,extended=TRUE)