This book introduces basic concepts, principle, and methods of medical statistics systematically and practically, especially in the statistical design of the experiment in terms of the specific problems, adequate use of statistical methods based on actual data and the reasonable explanation for statistical results.
This textbook combines statistical methods with the common application of SPSS software, which is flexible, convenient, and user-friendly; thus, students can focus on the deep understanding of statistics.
The authors emphasize the application and generalization of statistical methods, and combine these methods with the modern statistical theory, such as sequential contingency table and multivariate statistical modelling, etc.
This book is a useful textbook for graduate and undergraduate students in medical schools, including MBBS (Bachelor of Medicine and Bachelor of Surgery) student.
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Editor Xiuhua Guo is a doctor and professor of Epidemiology and Health Statistics, Capital Medical University, Beijing, China. The main research areas focus on the hierarchical data model or data mining model to handle big data of high dimensional environmental and genetic factors in major infectious diseases, cardiovascular diseases and metabolic disorders, thus to provide scientific proof for the causes of diseases and intervention strategies.
This book introduces basic concepts, principle, and methods of medical statistics systematically and practically, especially in the statistical design of the experiment in terms of the specific problems, adequate use of statistical methods based on actual data and the reasonable explanation for statistical results.
This textbook combines statistical methods with the common application of SPSS software, which is flexible, convenient, and user-friendly; thus, students can focus on the deep understanding of statistics.
The authors emphasize the application and generalization of statistical methods, and combine these methods with the modern statistical theory, such as sequential contingency table and multivariate statistical modelling, etc.
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