SCIENTIFIC DATA ANALYSIS WITH R

SCIENTIFIC DATA ANALYSIS WITH R

BIOSTATISTICAL APPLICATIONS
By AZIZUR RAHMAN , FARUQ ABDULLA , MD MOYAZZEM HOSSAIN
Rs.35,750
  • Availability: In Stock

Description

In an era marked by exponential growth in data generation and an unprecedented convergence of technology and healthcare, the intersection of biostatistics and data science has become a pivotal domain. This book is the ideal companion in navigating the convergence of statistical methodologies and data science techniques with diverse applications implemented in the open-source environment of R. It is designed to be a comprehensive guide, marrying the principles of biostatistics with the practical implementation of statistics and data science in R, thereby empowering learners, researchers, and practitioners with the tools necessary to extract meaningful knowledge from biological, health, and medical datasets. 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. It is useful for those seeking to understand the basics of data science and statistical analysis, or looking to enhance their skills in handling any simple or complex data including biological, health, medical, and industry data.

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Book Details

About the Author

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.

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