Statistics for Laboratory Scientists and Clinicians: A Practical Guide

Description

Understanding the underlying principles of statistical techniques and effectively applying statistical methods can be challenging for researchers at all stages of their career. This concise, practical guide uses a simple, engaging approach to take scientists and clinicians working in laboratory-based life science and medical research through the steps of choosing and implementing appropriate statistical methods to analyse results. The author draws on her extensive experience of advising students and researchers over the past 30 years, breaking down complex concepts into easy-to-understand units. Practical examples using free online statistical tools are included throughout, with illustrations and diagrams employed to keep jargon to a minimum. Sample size calculations and considerations are covered in depth, and the book refers to types of data from experiments that clinicians and lab-based scientists are likely to encounter. Straightforward, accessible and encouraging throughout, this is a go-to reference for researchers who want to achieve statistical autonomy.

Anne McDonnell Sill is a statistician and epidemiologist in the Department of Surgery, Saint Agnes Hospital, Baltimore, MD, USA. She has previously worked as a Research Associate in the Department of Biostatistics at the Children's National Medical Centre, Washington D.C., at the Institute of Human Virology (IHV), University of Maryland, Baltimore, and at the Johns Hopkins School of Medicine and School of Hygiene, Baltimore. She has spent more than 30 years advising students, laboratory scientists and clinicians on experimental design and statistical analysis. She has also used her data management and clinical research experience to help implement public health programs globally, as a Consultant for the Centers for Disease Control (CDC).

'Most statistics textbooks intimidate the professionals who are the intended audience. Anne McDonnell Sill does a masterful job of explaining complex and sophisticated statistical ideas. Her writing is very clear and easy to follow. The book skips over some of the mathematical details that are now processed by statistical software. This book is a welcome addition for laboratory scientists, research clinicians, undergraduates, graduates, and medical students.' Hamid Ferdosi, George Washington University, Washington, DC