Data scientists spend more than two-thirds of their time cleaning, preparing, exploring, and visualizing data before it is ready for modeling and mining. This textbook covers the important steps of data preparation and exploration that anyone who deals with data should know. This textbook is an excellent companion text for our other textbook Introduction to Biomedical Data Science. The data preparation and exploration methods we include are spreadsheet and statistics package approaches, as well as the programming languages R and Python. The reader is introduced to the free stat packages Jamovi…mehr
Data scientists spend more than two-thirds of their time cleaning, preparing, exploring, and visualizing data before it is ready for modeling and mining. This textbook covers the important steps of data preparation and exploration that anyone who deals with data should know. This textbook is an excellent companion text for our other textbook Introduction to Biomedical Data Science. The data preparation and exploration methods we include are spreadsheet and statistics package approaches, as well as the programming languages R and Python. The reader is introduced to the free stat packages Jamovi and BlueSky Statistics. Multiple techniques for data visualization are presented. Medical datasets are used for demonstrations and student exercises. Importantly, chapter content is supplemented with YouTube videos. Chapters are well referenced (100+) and there is a chapter on health data resources so the reader can find data to prepare and explore on their own. Prominent issues such as how to handle missing data and imbalanced datasets are covered along with sections on descriptive statistics, visualization, correlations, handling duplicates and outliers, scaling, standardization, and much more. A downloadable Data Checklist is available on https://www.informaticseducation.orgHinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Robert E. Hoyt, MD, FACP, FAMIA, is an internal medicine physician who was in private practice for 15 years and served as a physician in the military for 20 years. During this time, he taught health informatics for 13 years at the University of West Florida. He has been involved in health informatics for the past two decades, but in the last five years, he has focused primarily on biomedical data science, with emphasis on machine learning and artificial intelligence. He is a co-author and co-editor of Health Informatics: Practical Guide that is in its seventh edition. Additionally, he is the co-editor and co-author of the Introduction to Biomedical Data Science with Robert Muenchen that launched in 2019. Robert A. Muenchen, MS, PSA, is the author of the BlueSky Statistics 7.1 User Guide, R for SAS and SPSS Users, and coauthor of R for Stata Users and Introduction to Biomedical Data Science. An ASA Accredited Professional Statistician, Bob wrote or co-authored over 70 articles published in scientific journals and conference proceedings. At the University of Tennessee, he guided more than 1,000 graduate theses and dissertations and he continues to teach R workshops there.
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