# Null Hypothesis Significance Testing

NHST is used to determine whether the observed value of a network measure is larger, or smaller, or similar to, what is expected by chance. The function to perform a test is typically applied after you have generated randomized networks using either null models or network permutations.

#
** EcologicalNetwork.test_network_property** —

*Function*.

**Null Hypothesis Significance Testing**

test_network_property(N::EcoNetwork, f, S; test::Symbol=:greater)

Test whether the observed value (through applying a function `f`

) on an empirical network `N`

differs from the distribution derived from measuring the same value on a collection of randomized networks `S`

. `S`

is an array of networks of the same type as `N`

.

There are two possible values for the `test`

keyword argument: `:greater`

and `:smaller`

. The test is one-tailed. The results are returned as a `NetworkTestOutput`

object (see `?EcologicalNetwork.NetworkTestOutput`

for the complete edocumentation).

The *p*-value (`pval`

) is measured by counting the proportion of networks with a larger (resp. smaller) value of the measure than the original network, as in normal permutation tests.

The original value of the measure is given (`v0`

), as well as the *z*-scores (`z`

) of all randomized networks.

The output is a `NetworkTestOutput`

object, with a number of fields.

#
** EcologicalNetwork.NetworkTestOutput** —

*Type*.

**Output of a permutation-based test**

`pval`

– the test p-value`test`

– the type of test (`:smaller`

or`:greater`

)`v0`

– the measure of the empirical network`n`

– the number of randomized networks used`hits`

– the number of randomized network matching the test condition`z`

– the*z*-scores of the statistics for each randomized network