Introduction to Bio-Medical Data Analysis with R: Biodata R

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Bol This book includes a series of hands-on practical introductory guides to analyze bio-medical data using R, mainly for use by bio-medical students and researchers. It will provide readers with basic statistical programming skills in R, brought together with practical data analysis skills and applied statistical knowledge. The knowledge and skills to be gained from this book are also useful and applicable for those who use other statistical software.Data analysis is at the heart of modern biomedical research, and R is the tool that makes it possible. This hands-on, practical guide introduces researchers, clinicians, and students in the health sciences to R programming and applied biostatistics from the ground up. No prior programming experience is required. Structured in three progressive parts-foundational R skills, core statistical methods (linear and logistic regression, survival analysis, longitudinal data analysis), and advanced specialized topics (large consortium data, child growth, clinical trials, microbiome data analysis)-every chapter features real biomedical datasets, worked R code, and practice exercises. Whether you are transitioning from SPSS, Stata, or SAS, or are new to programming entirely, this book gives you the practical skills to take full control of your research data-from cleaning and visualization to complex modeling and reporting.

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This book includes a series of hands-on practical introductory guides to analyze bio-medical data using R, mainly for use by bio-medical students and researchers. It will provide readers with basic statistical programming skills in R, brought together with practical data analysis skills and applied statistical knowledge. The knowledge and skills to be gained from this book are also useful and applicable for those who use other statistical software.Data analysis is at the heart of modern biomedical research, and R is the tool that makes it possible. This hands-on, practical guide introduces researchers, clinicians, and students in the health sciences to R programming and applied biostatistics from the ground up. No prior programming experience is required. Structured in three progressive parts-foundational R skills, core statistical methods (linear and logistic regression, survival analysis, longitudinal data analysis), and advanced specialized topics (large consortium data, child growth, clinical trials, microbiome data analysis)-every chapter features real biomedical datasets, worked R code, and practice exercises. Whether you are transitioning from SPSS, Stata, or SAS, or are new to programming entirely, this book gives you the practical skills to take full control of your research data-from cleaning and visualization to complex modeling and reporting.


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Merk MDPI AG
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  • 9783725853380
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