Logic and Critical Thinking in the Biomedical Sciences (e-bog) af Berman, Jules J.
Berman, Jules J. (forfatter)

Logic and Critical Thinking in the Biomedical Sciences e-bog

1021,49 DKK (inkl. moms 1276,86 DKK)
All too often, individuals engaged in the biomedical sciences assume that numeric data must be left to the proper authorities (e.g., statisticians and data analysts) who are trained to apply sophisticated mathematical algorithms to sets of data. This is a terrible mistake. Individuals with keen observational skills, regardless of their mathematical training, are in the best position to draw cor...
E-bog 1021,49 DKK
Forfattere Berman, Jules J. (forfatter)
Udgivet 8 juli 2020
Længde 290 sider
Genrer Pre-clinical medicine: basic sciences
Sprog English
Format pdf
Beskyttelse LCP
ISBN 9780128213629
All too often, individuals engaged in the biomedical sciences assume that numeric data must be left to the proper authorities (e.g., statisticians and data analysts) who are trained to apply sophisticated mathematical algorithms to sets of data. This is a terrible mistake. Individuals with keen observational skills, regardless of their mathematical training, are in the best position to draw correct inferences from their own data and to guide the subsequent implementation of robust, mathematical analyses. Volume 2 of Logic and Critical Thinking in the Biomedical Sciences provides readers with a repertoire of deductive non-mathematical methods that will help them draw useful inferences from their own data.Volumes 1 and 2 of Logic and Critical Thinking in the Biomedical Sciences are written for biomedical scientists and college-level students engaged in any of the life sciences, including bioinformatics and related data sciences. Demonstrates that a great deal can be deduced from quantitative data, without applying any statistical or mathematical analyses Provides readers with simple techniques for quickly reviewing and finding important relationships hidden within large and complex sets of data Using examples drawn from the biomedical literature, discusses common pitfalls in data interpretation and how they can be avoided