Statistics for Biomedical Engineers and Scientists

How to Visualize and Analyze Data
Erscheinungsjahr 2019
ISBN: 978-0-08-102939-8
Verlag: Elsevier Science & Technology

Buch, Englisch, 274 Seiten, Format (B × H): 205 mm x 241 mm, Gewicht: 594 g

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.

Zielgruppe

<p>Biomedical; Engineers, biomedical sciences; Students, researchers</p>

Autoren/Hrsg.

King, Andrew P.

Eckersley, Robert

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Epidemiologie, Medizinische Statistik
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik

Inhaltsverzeichnis

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

Über Autor(innen)

Eckersley, Robert
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.

King, Andrew P.
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).