Debunking Seven Terrorism Myths Using Statistics

Author:   Andre Python
Publisher:   Taylor & Francis Ltd
ISBN:  

9780367472283


Pages:   150
Publication Date:   10 July 2020
Format:   Hardback
Availability:   In Print   Availability explained
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Debunking Seven Terrorism Myths Using Statistics


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Author:   Andre Python
Publisher:   Taylor & Francis Ltd
Imprint:   Chapman & Hall/CRC
Weight:   0.358kg
ISBN:  

9780367472283


ISBN 10:   0367472287
Pages:   150
Publication Date:   10 July 2020
Audience:   General/trade ,  College/higher education ,  Professional and scholarly ,  General ,  Tertiary & Higher Education
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Reviews

The book presents incredibly fascinating research, and can be interesting and useful not only to specialists but to general public for understanding and making informed judgments on terrorism and its debunking with help of statistical data analysis and prediction to prevent future attacks...Each chapter suggests mathematical definitions, glossary, and additional reading sources. Besides those, the book supplies with bibliography of 153 most recent works and multiple links to the internet sites.. ~Technometrics


Author Information

Andre Python is ZJU100 young professor of Statistics at Zhejiang University. His current research interests are in extending statistical models to address policy-relevant issues raised by the spread of phenomena threatening global security and health. In 2017, Andre completed a PhD in Statistics at the University of St Andrews, applying a Bayesian spatiotemporal model to capture fine-scale patterns of non-state terrorism across the world. As postdoctoral researcher at the University of Oxford, he has developed geostatistical models and actively contributed to the design and teaching of Bayesian statistics and R software courses for PhD students and University staff.

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