<!DOCTYPE rkhelp>
<document>
	<summary>
		This plugin calculates a Jarque-Bera chi-squared statistic for a variable x and tests against the null hypothesis of normality.
	</summary>

	<usage>
		Select one or more numeric variables to test against normality. An individual test is run for each one of them. The output consists of the JB chi-squared statistic with 2 degrees of freedom and its correspondent p-value.
		
		The statistic's distribution is asynthotic, so this test performs better when working with big samples.

		Make sure the data does not contain NAs or, if so, that the 'Exclude NAs' option is checked, as neglecting this will usually prevent the test from succeeding.
	</usage>

	<settings>
		<setting id="x">Select the data to be computed (one or more variables). The vectors need to be numeric and can be of different length.</setting>
		<setting id="length">Select if you want to include the number of observations and NAs in the output. (Default: YES)</setting>
		<setting id="excludenas">Select if your data has missing values. The NAs are then omitted when performing the test. (Default: YES)</setting>
	</settings>
	<related>
		<ul>
			<li><link href="rkward://rhelp/jarque.bera.test"/></li>
		</ul>
	</related>
</document>
