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Outlier Detection with Dixon-type (Q) tests
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:doc:`/SingleStepClassifiers/NonCausalStep/index`

This step detects outliers by comparing a ratio of ranges to an established table of values to determine whether the value in question is an outlier.

.. rubric:: Input Parameters

1. Input data including outliers

.. rubric:: Output Parameters

1. Original data with outliers marked

.. rubric:: Workflow

.. image:: workflow.svg


.. rubric:: Algorithm

:doc:`/Algorithms/DixonTypeQTests/index`

.. rubric:: References

- S.\  Walfish, A review of statistical outlier methods. Pharmaceutical Technology, 2006. Retrieved from www.pharmtech.com.