cramer

Computes the Cramer's V statistic and Chisquare p value between two categorical variables in data.frame.

A collection of tools that support data diagnosis, exploration, and transformation.
Data diagnostics provides information and visualization of missing values, outliers, and unique
and negative values to help you understand the distribution and quality of your data.
Data exploration provides information and visualization of the descriptive statistics of
univariate variables, normality tests and outliers, correlation of two variables,
and the relationship between the target variable and predictor. Data transformation supports binning
for categorizing continuous variables, imputes missing values and outliers, and resolves skewness.
And it creates automated reports that support these three tasks.

Choonghyun Ryu

dlookr

Tools for Data Diagnosis, Exploration, Transformation

cramer function

<dl><dt>dfm</dt>
<dd>data.frame. probability distributions.</dd>
<dt>x</dt>
<dd>character. name of categorical or discrete variable.</dd>
<dt>y</dt>
<dd>character. name of another categorical or discrete variable.</dd></dl>

Arguments

Cramer's V statistic — cramer

<dl>

<dt>dfm</dt>
<dd>data.frame. probability distributions.</dd>


<dt>x</dt>
<dd>character. name of categorical or discrete variable.</dd>


<dt>y</dt>
<dd>character. name of another categorical or discrete variable.</dd>

</dl>

cramer: Cramer's V statistic

Description

Usage

Value

Arguments

See Also

Examples