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ISSN: 2329-6895

Journal of Neurological Disorders
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Editorial

How Much would you Rely on Statistical Data? The Power of Statistical Analysis towards Truth as Well as Lie

Petridis AK*
Department of Neurosurgery, Sana Kliniken, Zu den Rehwiesen 9, P.O Box: 47055, Duisburg, Germany
Corresponding Author : Dr. Athanasios K. Petridis
Department of Neurosurgery, Sana Kliniken
Zu den Rehwiesen 9, 47055, Duisburg, Germany
Tel: 492037332425
Fax: 492037330
E-mail: [email protected]
Received June 09, 2015; Accepted June 11, 2015; Published June 13, 2015
Citation: Petridis AK (2015) How Much would you Rely on Statistical Data? The Power of Statistical Analysis towards Truth as Well as Lie. J Neurol Disord 3:e116. doi: 10.4172/2329-6895.1000e116
Copyright: © 2015 Petridis AK. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Abstract

Background: Statistics is a powerfull tool in the hands of an expert but in the hands of a fool it can result in devastating conclusions, since it can fool the whole scientific world.

Method: A simulation of 340 patients with growth hormone overexpression and visual disturbance is compared with a control group of normal expressing growth hormone in healthy individuals. Different statistical analyses have been performed.

Results: All statistical analyses performed here, show a highly significant correlation of growth hormone overexpression and visual disturbance.

Conclusion: Statistically it seems that growth hormone is a cause of visual disturbance. We know that growth hormone by itself is not causing blindness but the disease hidden behind this overexpression, namely macro adenomas does. Would we not be aware of the causative disease we would easily come to the conclusion that growth hormone is strongly associated with visual disturbance. If the knowledge about a pathologic entity is incomplete a statistical analysis alone can mislead the scientific world to very strange conclusions.

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