Introduction to Statistics for Biomedical Engineers

There are many books written about statistics, some brief, some detailed, some humorous, some colorful, and some quite dry. Each of these texts is designed for a specific audience. Too often, texts about statistics have been rather theoretical and intimidating for those not practicing statistical analysis on a routine basis. Thus, many engineers and scientists, who need to use statistics much more frequently than calculus or differential equations, lack sufficient knowledge of the use of statistics. The audience that is addressed in this text is the university-level biomedical engineering student who needs a bare-bones coverage of the most basic statistical analysis frequently used in biomedical engineering practice. The text introduces students to the essential vocabulary and basic concepts of probability and statistics that are required to perform the numerical summary and statistical analysis used in the biomedical field. This text is considered a starting point for important issuesto consider when designing experiments, summarizing data, assuming a probability model for the data, testing hypotheses, and drawing conclusions from sampled data. A student who has completed this text should have sufficient vocabulary to read more advanced texts on statistics and further their knowledge about additional numerical analyses that are used in the biomedical engineering field but are beyond the scope of this text. This book is designed to supplement an undergraduate-level course in applied statistics, specifically in biomedical engineering. Practicing engineers who have not had formal instruction in statistics may also use this text as a simple, brief introduction to statistics used in biomedical engineering. The emphasis is on the application of statistics, the assumptions made in applying the statistical tests, the limitations of these elementary statistical methods, and the errors often committed in using statistical analysis. A number of examples from biomedical engineering research and industry practice are provided to assist the reader in understanding concepts and application. It is beneficial for the reader to have some background in the life sciences and physiology and to be familiar with basic biomedical instrumentation used in the clinical environment. Contents: Introduction / Collecting Data and Experimental Design / Data Summary and Descriptive Statistics / Assuming a Probability Model from the Sample Data / Statistical Inference / Linear Regression and Correlation Analysis / Power Analysis and Sample Size / Just the Beginning / Bibliography

Autorentext

Kristina M. Ropella is currently a professor of biomedical engineering at Marquette University, where she has been a member of the faculty since 1990. She received her Doctor of Philosophy degree in biomedical engineering from Northwestern University (Evanston, IL). Her research interests are in physiological signal processing, electrophysiology of heart and brain, functional magnetic resonance imaging, and biocomputing. She teaches undergraduate and graduate courses in biomedical signal processing, statistical time series analysis, biostatistics, biomedical computing, and biomedical instrumentation design. She is a past recipient of the Marquette University Robert and Mary Gettel Faculty Award for Teaching Excellence and the College of Engineering Out[1]standing Teacher award. She also directs the Functional Imaging Program, a joint doctoral degree program offered by Marquette University and the Medical College of Wisconsin. She is a fellow of the American Institute of Medical and Biological Engineering, a senior member of the IEEE Engineering in Medicine and Biology Society, and a member of the Biomedical Engineering Society and the American Society for Engineering Education. She serves on the editorial board for IEEE Book Press, biomedical engineering series, and she has chaired a number of education- and university industry-related sessions at the EMBS, BMES, and ASEE society meetings. Her personal interests include raising three children, racquetball, dance, travel, and lay ministry for the church.

Inhalt
Contents: Introduction.- Collecting Data and Experimental Design.- Data Summary and Descriptive Statistics.- Assuming a Probability Model from the Sample Data.- Statistical Inference.- Linear Regression and Correlation Analysis.- Power Analysis and Sample Size.- Just the Beginning.- Bibliography.