# summary.freqtab: Descriptive Statistics for Frequency Tables In equate: Observed-Score Linking and Equating

## Description

These functions return descriptive statistics for a frequency table of class “`freqtab`”.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26``` ```## S3 method for class 'freqtab' summary(object, margin = seq(margins(object)), ...) ## S3 method for class 'freqtab' mean(x, margin = 1, ...) sd.freqtab(x, margin = 1) var.freqtab(x, margin = 1) cov.freqtab(x, margin = seq(margins(x))) cor.freqtab(x, margin = seq(margins(x))) ## S3 method for class 'freqtab' min(x, margin = 1, ..., na.rm = FALSE) ## S3 method for class 'freqtab' max(x, margin = 1, ..., na.rm = FALSE) ## S3 method for class 'freqtab' range(x, margin = 1, ..., na.rm = FALSE) skew.freqtab(x, margin = 1) kurt.freqtab(x, margin = 1) ```

## Arguments

 `object, x` object of class “`freqtab`”. `margin` integer vector specifying the margin(s) for which summary statistics will be returned. This defaults to `1` for univariate statistics, and `seq(margins(x))`, i.e., all the margins, for multivariate statistics (covariance and correlation). `...` further arguments passed to or from other methods. `na.rm` logical indicating whether missing values should be removed, currently ignored since frequency tables cannot contain missing values.

## Details

`mean`, `sd.freqtab`, `var.freqtab`, `skew.freqtab`, and `kurt.freqtab` return the mean, standard deviation, variance, skewness, and kurtosis. `min` and `max` return the minimum and maximum observed scores, and `range` returns both. `cov.freqtab` and `cor.freqtab` return the covariance and correlation matrices for one or more variables. `summary` returns univariate statistics across one or more margins.

## Value

`summary` returns a data frame of summary statistics, including the mean, standard deviation, skewness, kurtosis, minimum, maximum, and number of observations for each variable in `margin`. Otherwise, a vector of length `length(margin)` is returned with the corresponding statistic for each variable.

## Author(s)

Anthony Albano [email protected]

`freqtab`
 ```1 2 3 4 5``` ```summary(as.freqtab(ACTmath[, 1:2])) ny <- freqtab(KBneat\$y, scales = list(0:36, 0:12)) summary(ny) cov.freqtab(ny) ```