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Présentation Scientific Data Analysis With R de Abdulla, Faruq Format Relié
- Livre Médecine, Pharmacie, Paramédical, Médecine vétérinaire
Résumé : Azizur Rahman is a professor at the School of Computing, Mathematics and Engineering and the 'Data Mining Research Group' leader at Charles Sturt University, Australia. He earned a BSc (Honours) in Statistical Science, an MSc (Thesis) in Biostatistics, and a PhD in Economics and Statistics from the University of Canberra under the supervision of Professor Ann Harding, AO FASSA. He worked as a biostatistical research fellow in the Faculty of Health and Medical Sciences at the University of Adelaide. Professor Rahman is a statistician and data scientist with expertise in developing and applying novel methodologies, models, and technologies. He designs projects to understand multidisciplinary research issues within various fields with the interaction or adaptation of statistics, data science, AI, and ML. Professor Rahman develops data-centric 'alternative computational methods in microsimulation modelling technologies', which are handy tools for decision-making processes in government and nongovernmental organizations, precision estimation, policy analysis, and evaluation. He founded and runs the 'Data Analytics Lab' at Charles Sturt. Professor Rahman has accrued more than $4.03 million of external research funding and over 213 scholarly publications and received several awards, including the ANZRSAI's 2023 Outstanding Service Award and the Charles Sturt Excellence Awards 2023 and 2024. Faruq Abdulla is an outstanding graduate researcher, statistician, and data scientist, adeptly practicing in academia and industry. His expertise includes applying and developing sophisticated statistical, data science, and machine learning methodologies, models, and techniques in biological and medical sciences. With a keen focus on high-dimensional simulation and real-world data, he tackles pressing public health challenges, thereby contributing to evidence-based policy formulation. He has completed an MSc (Thesis) and a BSc (Honors) in Statistics from the Islamic University, Kushtia, Bangladesh. His academic excellence is evident through his first place in his class in order of merit at both the BSc and MSc levels, earning him the prestigious Presidential Gold Medal for achieving the highest marks in the Faculty of Applied Science & Technology in the MSc final examination. Moreover, Abdulla actively contributes to the scientific community by advancing scientific knowledge through his research findings published in renowned international peer-reviewed and high-impact journals indexed in SCOPUS and SCI. Additionally, he serves as a discerning reviewer for esteemed peer-reviewed journals published by world-class publishers. Md. Moyazzem Hossain is an applied statistician and data scientist specializing in developing and applying contemporary statistical and data science methodologies, models, and techniques and currently holding the position of Professor in the Department of Statistics and Data Science at Jahangirnagar University, Bangladesh. Hossain earned his PhD from the School of Mathematics, Statistics, and Physics at Newcastle University, UK. He also obtained his BSc (Honors), MSc (Thesis), and MPhil from the Department of Statistics, Jahangirnagar University, Bangladesh. Hossain's outstanding contributions have been recognized through accolades such as the 'Best Conference Paper' award at the Australia and New Zealand Regional Science Association International 45th Annual Conference, held at Charles Sturt University, Wagga Wagga, Australia, on 1-2 December 2022. His research findings have been disseminated through numerous peer-reviewed publications in esteemed journals. Additionally, Hossain has served as an academic editor for PloS ONE and contributed as a reviewer for various international journals.
Sommaire:
This book is intended for students, researchers, and professionals eager to harness the combined power of biostatistics, data science, and the R programming language while gathering vital statistical knowledge needed for cutting-edge scientists in all fields....
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