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Applied medical statistics / Jingmei Jiang
Hoboken, NJ : John Wiley & Sons, Inc, 2022
xvii, 565 pages. : illustrations ; 24 cm.
Ký hiệu phân loại (DDC): 610.285
Over the past few decades, biomedical data have proliferated rapidly, and opportunities have arisen to use this data to improve human health. Burgeoning methods, such as machine learning techniques, have emerged to respond to the fast growth of the volume of data, and to exploit data in an effective and efficient manner. These methods were founded on statistical learning theory, which is an expansion of traditional statistics. Therefore, cultivating basic statistical thinking capability plays an important and fundamental role in mastering these state-of-the-art methods and embracing the upcoming big data era, which makes a course of introductory biostatistics an indispensable part of the curriculum for medical students. However, as a branch of mathematics, statistics is characterized by hierarchically organized concepts, but a conceptual understanding of statistics is not always intuitive, which makes biostatistics an obstacle that is regarded as a burden for most medical students
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