# Normality Test Calculator – Anderson Darling

Instructions: Using this Normality Test Calculator to enter the sample data in the form below, and this calculator will conduct a normality test (Anderson-Darling) to assess whether or not the sample data provided departs significantly from normality

Type the sample (comma or space separated)
Name of the variable (Optional)
Significance Level ($$\alpha$$)

## Normality Test Calculator

A normality test is a statistical hypothesis test that assess whether or not a sample of data departs significantly from normality or not. For a given sample $$X_i$$, the purpose of the test is to assess whether the data depart significantly from normality or not.

This normality test will test the following null and alternative hypothesis:

$$H_0:$$ The sample data comes from a normally distributed population

$$H_A:$$ The sample data does not come from a normally distributed population

In order to conduct the Anderson-Darling (AD) test, the following test statistic is computed:

$A^2 = -n - \frac{1}{n}\sum_{i=1}^{n}\left((2i-1)\ln\Phi(Z_i) + (2(n-i)+1)\ln(1- \Phi(Z_i))\right) \left(1 + \frac{0.75}{n} - \frac{2.25}{n^2} \right)$

There are other normality tests you may be interested in taking a look, such as the Shapiro-Wilk and the Kolmogorov-Smirnov normality test.

If you need assess the properties of the distribution of $$X_i$$, you can use our box plot chart maker and our histogram maker.

In case you have any suggestion, or if you would like to report a broken solver/calculator, please do not hesitate to contact us.