Statistics for Data Science and Policy Analysis (PDF)
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This book brings together the best contributions of the Applied Statistics and Policy Analysis Conference 2019. Written by leading international experts in the field of statistics, data science and policy evaluation. This book explores the theme of effective policy methods through the use of big data, accurate estimates and modern computing tools and statistical modelling.
Associate Professor Azizur Rahman, PhD, is an applied statistician and data scientist with expertise in both developing and applying novel methodologies, models and technologies. He is the Leader of "Statistics and Data Mining Research Group" in the Faculty of Business, Justice and Behavioural Sciences at the Charles Sturt University (CSU). Prof. Rahman is able to assist in understanding multi-disciplinary research issues within various fields including how to understand the individual activities which occur within very complex scientific, behavioural, socio-economic and ecological systems.
He develops "alternative methods in microsimulation modelling technologies" which are very useful tools to socioeconomic policy analysis and evaluation. His 2016 book has contributed significantly to the field of small area estimation and microsimulation modelling. Prof. Rahman's research interests encompass issues in simple to multi-facet analyses in various fields ranging from the mathematical sciences to the law and legal studies. He has more than 100 scholarly publications including a few books. Prof. Rahman's research is funded by the Australian Federal and State Governments, and he serves on a range of editorial boards including the International Journal of Microsimulation (IJM) and Sustaining Regions. He obtained several awards including the SOCM Research Excellence Award 2018 and the CSU-RED Achievement Award 2019.
- 2020, 1st ed. 2020, 386 Seiten, Englisch
- Herausgegeben: Azizur Rahman
- Verlag: Springer-Verlag GmbH
- ISBN-10: 9811517355
- ISBN-13: 9789811517358
- Erscheinungsdatum: 31.03.2020
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- Dateiformat: PDF
- Größe: 7.37 MB
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