Applied medical statistics / Jingmei Jiang.
By: Jiang, Jingmei [author.]
Language: English Publisher: Hoboken, NJ : John Wiley & Sons, Inc., 2022Copyright date: ©2022Description: 1 online resource (xvii, 565 pages) : illustrationsContent type: text Media type: computer Carrier type: online resourceISBN: 9781119716709 ; 9781119716822; 1119716829; 9781119716778; 1119716772; 1119716799; 9781119716792Subject(s): Medicine -- Research -- Statistical methods -- Textbooks | Medical statistics -- Textbooks | Biometry -- Textbooks | Biometry -- methods | Statistics as TopicGenre/Form: Electronic books. | Textbooks. | Textbooks.DDC classification: 610.72/7 LOC classification: R853.S7 | J53 2022Online resources: Full text is available at Wiley Online Library Click here to view Summary: "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"-- Provided by publisher.| Item type | Current location | Home library | Call number | Status | Date due | Barcode | Item holds |
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EBOOK
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COLLEGE LIBRARY | COLLEGE LIBRARY | 610.727 J56 2022 (Browse shelf) | Available |
Includes bibliographical references and index.
"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"-- Provided by publisher.
About the Author
Jingmei Jiang is a Professor of Biostatistics in Department of Epidemiology and Biostatistics, as well as a Doctoral Tutor in the Institute of Basic Medical Sciences of CAMS & School of Basic Medicine of PUMC. Currently, she is the Director of Statistics section, and an editorial board member of several journals including two international journals. In recent years, she has been undertaking a number of research projects at the National Natural Science Foundation of China, Special Program Foundation of Ministry of Health, and Special Program Foundation for Basic Research of Ministry of Science and Technology of China.
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