Statistics for Laboratory Scientists and Clinicians
A Practical Guide

Uses practical examples to teach laboratory scientists and research clinicians how to accomplish statistical tasks confidently.

Anne McDonnell Sill (Author)

9781108477253, Cambridge University Press

Hardback, published 8 July 2021

174 pages
23.5 x 15.6 x 1.3 cm, 0.41 kg

'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

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.

Preface
Acknowledgements
Part I. Basic Statistical Concepts: 1. Understanding some Basic Statistical Tests and Concepts
2. Types of Data and their Distributions
3. Significance Testing
Part II. What is the Right Statistical Test for Different Types of Data: 4. Analyzing Continuous Data
5. Analyzing Non-normally Distributed, Continuous Data – Non-parametric Tests
6. Analyses for Non-continuous Data
7. Analyzing a Combination of Data Types
Part III. Applied Statistics: 8. Applied Statistics for the Laboratorian
9. Applied Statistics for the Clinician
10. Interpreting Graphs and Charts
Glossary
Figure Credits
Index.

Subject Areas: Life sciences: general issues [PSA], Mathematics & science [P], Epidemiology & medical statistics [MBNS]