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Logic and Critical Thinking in the Biomedical Sciences - 1st Edition - ISBN: 9780128213698

Logic and Critical Thinking in the Biomedical Sciences

1st Edition

Volume 2: Deductions Based Upon Quantitative Data

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Author: Jules Berman
Paperback ISBN: 9780128213698
Imprint: Academic Press
Published Date: 24th July 2020
Page Count: 290
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Logic and Critical Thinking in the Biomedical Sciences, Volume Two: Deductions Based upon Quantitative Data provides biomedical students and scientists with a repertoire of deductive non-mathematical methods to help them draw useful inferences from their own data. The book tackles the challenges that arise when available data is quantitative, not descriptive. This updated volume provides readers with a set of non-mathematical skills that allows them to not only understand information but also draw valid inferences from numeric data. This book is a valuable source for members of the biomedical field who want to understand how to interpret the medical data currently available.

Key Features

  • Provides a serious and scientific based discussion on deductive methods in the biomedical sciences
  • Discusses deduction with a linear and coherent narrative, helping readers engage on a complex, but neglected topic
  • Presents examples and case studies in a relaxed manner, covering general concepts without excessively dwelling on details


Bioinformaticians; biostatisticians; graduate students; medical students. Members of biomedical field in general who deal with data

Table of Contents

9. Learning what counting tells us
10. Drawing inferences from absences of data values
11. Drawing Inferences from Data Ranges
12. Drawing inferences from outliers and exceptions
13. What we learn when the bell curve won't fit our data
14. Resolving cause and effect puzzles with time-stamped data
15. Heuristic methods that use random numbers


No. of pages:
© Academic Press 2020
24th July 2020
Academic Press
Paperback ISBN:

About the Author

Jules Berman

Jules J. Berman received two baccalaureate degrees from MIT; in Mathematics, and in Earth and Planetary Sciences. He holds a PhD from Temple University, and an MD, from the University of Miami. He was a graduate student researcher in the Fels Cancer Research Institute, at Temple University, and at the American Health Foundation in Valhalla, New York. His postdoctoral studies were completed at the US National Institutes of Health, and his residency was completed at the George Washington University Medical Center in Washington, DC. Dr. Berman served as Chief of Anatomic Pathology, Surgical Pathology, and Cytopathology at the Veterans Administration Medical Center in Baltimore, Maryland, where he held joint appointments at the University of Maryland Medical Center and at the Johns Hopkins Medical Institutions. In 1998, he transferred to the US National Institutes of Health, as a Medical Officer, and as the Program Director for Pathology Informatics in the Cancer Diagnosis Program at the National Cancer Institute. Dr. Berman is a past president of the Association for Pathology Informatics, and the 2011 recipient of the Association's Lifetime Achievement Award. He has first-authored more than 100 journal articles and has written 18 science books. His most recent titles, published by Elsevier, include:

-Taxonomic Guide to Infectious Diseases: Understanding the Biologic Classes of Pathogenic Organisms, 1st edition (2012)
-Principles of Big Data: Preparing, Sharing, and Analyzing Complex Information (2013)
-Rare Diseases and Orphan Drugs: Keys to Understanding and Treating the Common Diseases (2014)
-Repurposing Legacy Data: Innovative Case Studies (2015)
-Data Simplification: Taming Information with Open Source Tools (2016)
-Precision Medicine and the Reinvention of Human Disease (2018)
-Principles and Practice of Big Data: Preparing, Sharing, and Analyzing Complex Information, Second Edition (2018)
-Taxonomic Guide to Infectious Diseases: Understanding the Biologic Classes of Pathogenic Organisms, 2nd edition (2019)

Affiliations and Expertise

Author with expertise in informatics, computer programming, and cancer biology

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