# cont_table: Contingency table In descstat: Tools for Descriptive Statistics

## Description

A contingency table returns the counts of all the combinations of the modalities of two series in a table for which every modality of the first series is a row and every modality of the second series is a column. The `joint`, `marginal` and `conditional` functions compute these three distributions from the contingency table (by indicating one series for the last two).

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20``` ```cont_table( data, x1, x2, weights = NULL, freq = NULL, total = FALSE, xfirst1 = NULL, xlast1 = NULL, wlast1 = NULL, xfirst2 = NULL, xlast2 = NULL, wlast2 = NULL ) joint(data) conditional(data, x = NULL) marginal(data, x = NULL, f = "f", vals = NULL) ```

## Arguments

 `data` a tibble, `x1, x2` the two series used the construct the contingency table, the distinct values of the first and the second will respectively be the rows and the columns of the contingency table, `weights` a series containing the weights that should be used to mimic the population, `freq` the frequencies (in the case where data is already contingency table), `total` if `TRUE`, a total is added to the table, `xfirst1, xfirst2, xlast1, xlast2, wlast1, wlast2` see `as_numeric()`, `x` the series on which the operation should be computed, `f` see `freq_table()`, `vals` see `freq_table()`,

## Details

`cont_table` actually returns a tibble in "long format", as the `dplyr::count` table does. As the returned object is of class `cont_table`, this is the `format` and `print` methods that turns the tibble in a wide format before printing.

The `conditional` and `joint` functions return a `cont_table` object, as the `marginal` function returns a `freq_table` object.

a tibble

Yves Croissant

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10``` ```library("dplyr") # get a contingency table containing education and sex cont_table(employment, education, sex) # instead of counts, sum the weights cont_table(employment, education, sex, weights = weights) # get the joint distribution and the conditional and marginal # distribution of sex cont_table(employment, education, sex) %>% joint cont_table(employment, education, sex) %>% marginal(sex) cont_table(employment, education, sex) %>% conditional(sex) ```

descstat documentation built on Feb. 17, 2021, 5:07 p.m.