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Practical Statistics In Medicine With R
Practical Statistics In Medicine With R
Practical Statistics In Medicine With R

Practical Statistics In Medicine With R

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Practical Statistics in Medicine with RUnderstanding Fundamental Concepts through Examples\nAuthor(s): Konstantinos I. Bougioukas\nFormat: Paperback\nPublisher: Taylor & Francis Ltd, United Kingdom\nImprint: Chapman & Hall/CRC\nISBN-13: 9781032602080, 978-1032602080\nSynopsis\nWhether youre new to statistical analysis or looking to enhance your analytical skills with the R programming language, this textbook provides comprehensive and practical guidance for understanding fundamental statistical concepts through healthcare examples in R. It is an ideal resource for students, educators, and healthcare researchers seeking a step-by-step first approach to effectively applying R in the analysis of healthcare data. \n\nReaders are introduced to the fundamentals of base R, along with practical methods for data import, preprocessing, and transformation using functions from standard R packages such as base and stats, as well as pipe-friendly functions from the tidyverse collection of .

Practical Statistics In Medicine With R

Practical Statistics in Medicine with RUnderstanding Fundamental Concepts through Examples\nAuthor(s): Konstantinos I. Bougioukas\nFormat: Paperback\nPublisher: Taylor & Francis Ltd, United Kingdom\nImprint: Chapman & Hall/CRC\nISBN-13: 9781032602080, 978-1032602080\nSynopsis\nWhether youre new to statistical analysis or looking to enhance your analytical skills with the R programming language, this textbook provides comprehensive and practical guidance for understanding fundamental statistical concepts through healthcare examples in R. It is an ideal resource for students, educators, and healthcare researchers seeking a step-by-step first approach to effectively applying R in the analysis of healthcare data. \n\nReaders are introduced to the fundamentals of base R, along with practical methods for data import, preprocessing, and transformation using functions from standard R packages such as base and stats, as well as pipe-friendly functions from the tidyverse collection of .

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