Statistics for Biomedical Engineers and Scientists: How to Analyze and Visualize Data provides an intuitive understanding of the concepts of basic statistics, with a focus on solving biomedical problems. Readers will learn how to understand the fundamental concepts of descriptive and inferential statistics, analyze data and choose an appropriate hypothesis test to answer a given question, compute numerical statistical measures and perform hypothesis tests 'by hand', and visualize data and perform statistical analysis using MATLAB. Practical activities and exercises are provided, making this an ideal resource for students in biomedical engineering and the biomedical sciences who are in a course on basic statistics.
- Presents a practical guide on how to visualize and analyze statistical data
- Provides numerous practical examples and exercises to illustrate the power of statistics in biomedical engineering applications
- Gives an intuitive understanding of statistical tests
- Covers practical skills by showing how to perform operations 'by hand' and by using MATLAB as a computational tool
- Includes an online resource with downloadable materials for students and teachers
1. Descriptive Statistics I: Univariate Statistics 2. Descriptive Statistics II: Bivariate Statistics 3. Descriptive Statistics III: ROC Analysis 4. Inferential Statistics I: Basic Concepts 5. Inferential Statistics II: Parametric Hypothesis Testing 6. Inferential Statistics III: Nonparametric Hypothesis Testing 7. Inferential Statistics IV: Choosing a Hypothesis Test 8. Inferential Statistics V: Multiple Hypothesis Testing 9. Experimental Design and Sample Size Calculations 10. Statistical Shape Models 11. Case Study on Descriptive and Inferential Statistics
Dr. King received a BSc. (Hons) degree in Computer Science from Manchester University in 1989, an MSc. (with distinction) in Cognition, Computing and Psychology from Warwick University in 1992, and a PhD degree in Computer Science from Warwick University in 1997. He has been a postdoctoral researcher with the Computational Imaging Sciences Group and the Division of Imaging Sciences at King's College London, working mainly on registration, image-guided interventions and soft-tissue modelling. From 2001-2005 he worked as an Assistant Professor in the Computer Science department at Mekelle University in Northern Ethiopia. His research focuses on motion estimation and modelling.
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.