Statistical Advances In The Biomedical Sciences

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Statistical Modeling for Biomedical Researchers

Author	: William D. Dupont
Publisher	: Cambridge University Press
Total Pages	: 543
Release	: 2009-02-12
ISBN-10	: 9780521849524
ISBN-13	: 0521849527
Rating	: 4/5 (527 Downloads)

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Book Synopsis Statistical Modeling for Biomedical Researchers by : William D. Dupont

Download or read book Statistical Modeling for Biomedical Researchers written by William D. Dupont and published by Cambridge University Press. This book was released on 2009-02-12 with total page 543 pages. Available in PDF, EPUB and Kindle. Book excerpt: A second edition of the easy-to-use standard text guiding biomedical researchers in the use of advanced statistical methods.

Statistical Modeling for Biomedical Researchers Related Books

Language: en
Pages: 543

Statistical Modeling for Biomedical Researchers

Authors: William D. Dupont

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Type: BOOK - Published: 2009-02-12 - Publisher: Cambridge University Press

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A second edition of the easy-to-use standard text guiding biomedical researchers in the use of advanced statistical methods.

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This edited collection discusses the emerging topics in statistical modeling for biomedical research. Leading experts in the frontiers of biostatistics and biom

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Statistical Advances in the Biomedical Sciences

Authors: Atanu Biswas

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The Most Comprehensive and Cutting-Edge Guide to Statistical Applications in Biomedical Research With the increasing use of biotechnology in medical research an

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Introductory Statistics for the Life and Biomedical Sciences

Authors: Julie Vu

Categories:

Type: BOOK - Published: 2020-03 - Publisher:

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Introduction to Statistics for the Life and Biomedical Sciences has been written to be used in conjunction with a set of self-paced learning labs. These labs gu

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Statistical Bioinformatics

Authors: Jae K. Lee

Categories: Medical

Type: BOOK - Published: 2011-09-20 - Publisher: John Wiley & Sons

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This book provides an essential understanding of statistical concepts necessary for the analysis of genomic and proteomic data using computational techniques. T