Statistics for Biomedical Engineers and Scientists

Dr King has over 20 years of experience of teaching computing courses at university level. He is currently a Reader in the Biomedical Engineering department at King's College London. With Paul Aljabar, he designed and developed the Computer Programming module for Biomedical Engineering students upon which this book was based. The module has been running since 2014 and Andrew still co-organises and teaches on it. Between 2001-2005, Andrew worked as an Assistant Professor in the Computer Science department at Mekelle University in Ethiopia, and was responsible for curriculum development, and design and delivery of a number of computing modules. Andrew's research interests focus mainly on the use of machine learning and artificial intelligence techniques to tackle problems in medical imaging, with a special focus on dynamic imaging data, i.e. moving organs (Google Scholar: https://goo.gl/ZZGrGr, group web site: http://kclmmag.org). Dr. Robert Eckersley is a Senior Lecturer in the School of Biomedical Engineering and Imaging Sciences at King’s College London. His research interests include all aspects of the physics and engineering of medical ultrasound imaging. He has a long standing interest in the development of microbubble contrast agents for quantitative functional imaging with ultrasound. He is currently PI on an EPSRC grant investigating the development of super-resolution strategies for ultrasound imaging and is an co-investigator on the Wellcome and EPSRC funded iFind project http://www.ifindproject.com.

"This book is a very interesting introduction to the basic concepts of statistics. The majority of examples are taken from medicine and biology. However, the scope of the book is more general, so it is worth to be read by everybody, who wants to apply statistical methods in any field." --zbMATH

• 1. Descriptive Statistics I: Univariate Statistics2. Descriptive Statistics II: Bivariate Statistics3. Descriptive Statistics III: ROC Analysis4. Inferential Statistics I: Basic Concepts5. Inferential Statistics II: Parametric Hypothesis Testing6. Inferential Statistics III: Nonparametric Hypothesis Testing7. Inferential Statistics IV: Choosing a Hypothesis Test8. Inferential Statistics V: Multiple Hypothesis Testing9. Experimental Design and Sample Size Calculations10. Statistical Shape Models11. Case Study on Descriptive and Inferential Statistics