Applied Medical Statistics (Original PDF From Publisher)
Written by Jingmei Jiang
MEDICAL STATISTICS APPLIED
A current examination of basic statistics and probability principles for researchers and medical students
Researchers and medical publications alike are realizing more and more how important it is to increase statistical rigor in medical
research.
Famous statistician and researcher Dr. Jingmei Jiang provides a concise, logical and approachable introduction to fundamental
statistical principles in Applied Medical Statistics, making it perfect for medical students and medical research professionals.
The book will aid readers in developing a critical knowledge of the fundamental assumptions behind statistical analysis approaches
as well as in mastering essential topics in statistical analysis.
The eminent author provides information without assuming any prior knowledge of probability, statistics or specialist mathematics.
To assist readers understand the principles and gain experience critically evaluating various research scenarios, exercises and
case discussions are included with the methodologies outlined, all of which are illustrated using current examples based on real-world
medical research.
The following will also be beneficial to readers: a comprehensive introduction to fundamental statistical ideas, covering location
and distribution of data distributions, estimation of population parameters, statistical hypothesis testing and foundational words
and definitions investigations of popular statistical techniques, including as linear regression, analysis of variance and t-tests
Advanced analysis issues such as survival analysis, logistic regression, and multiple linear regression and correlation are discussed.
At the conclusion of every chapter, there are meaningful activities and case discussions.
Applied Medical Statistics is an invaluable resource for physicians, postgraduate medical students, and medical and biomedical
researchers.
It should also be kept on the bookshelf of any researcher who is interested in biostatistics or using statistical techniques in their
own work.
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