Description
Book SynopsisBiomedical scientists are the foundation of modern healthcare, from cancer screening to diagnosing HIV, from blood transfusion for surgery to food poisoning and infection control. Without biomedical scientists, the diagnosis of disease, the evaluation of the effectiveness of treatment, and research into the causes and cures of disease would not be possible.The Fundamentals of Biomedical Science series has been written to reflect the challenges of practicing biomedical science today. It draws together essential basic science with insights into laboratory practice to show how an understanding of the biology of disease is coupled to the analytical approaches that lead to diagnosis. Assuming only a minimum of prior knowledge, the series reviews the full range of disciplines to which a Biomedical Scientist may be exposed - from microbiology to cytopathology to transfusion science. Data Handling and Analysis is the most relevant and useful statistics and data analysis text for biomedical sci
Trade ReviewA gem of a find! For once it makes statistics understandable and it also clearly explains research and professional practice. Few books cover this range of topics. It is ideal for students completing research and also introduces student to good clinical practice. The statistical sections are very well explained indeed and simplify complicated concepts in a very readable manner. * Ruth Shiner, University of Wolverhampton *
Provides clear explanations of basic statistical and experimental design concepts which are placed into a practical context that is highly relevant for BMS students * Lewis Bingle, University of Sunderland *
An easy-to-read book that explains how to use a range of statistical tests that can be applied to data * Amreen Bashir, Aston University *
Table of Contents1: Information in biomedical science 2: Handling quantities: mass, volume, and concentration 3: Obtaining and verifying data 4: Presenting data in graphical form 5: Quality, audit, and good laboratory practice 6: Research 1: Setting the scene 7: Research 2: The analysis of modest data sets 8: Research 3: Large data sets 9: Communication
