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- Author: Sylvia Wassertheil-Smoller
- Publisher: Springer
- ISBN-10: 303153042X
- ISBN-13: 9783031530425
- Format: 15.6 x 23.4 x 1.6 cm, kieti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
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Description
This book teaches foundations of epidemiological design and statistical methods, as well as including topics applicable to new areas of research. Since the publication of the first edition, Biostatistics and Epidemiology has attracted loyal readers from across specialty areas in the biomedical community. The Fifth Edition includes coverage of fixed and random effects and mixed effects models; Poisson regression; constructing confidence intervals for U-shaped relationships; analysis of rare variants; Mendelian randomization; and aspects of machine learning and big data analytics. Biostatistics and Epidemiology was written to be accessible for readers without backgrounds in mathematics. It provides clear explanations of underlying principles, as well as practical guidelines of "how to do it" and "how to interpret it." Key features include a philosophical and logical explanation at the beginning of the book, subsections that can stand alone or serve as reference, cross-referencing, recommended reading, and appendices covering sample calculations for various statistics in the text.
EXTRA 10 % discount with code: EXTRA
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- Author: Sylvia Wassertheil-Smoller
- Publisher: Springer
- ISBN-10: 303153042X
- ISBN-13: 9783031530425
- Format: 15.6 x 23.4 x 1.6 cm, kieti viršeliai
- Language: English English
This book teaches foundations of epidemiological design and statistical methods, as well as including topics applicable to new areas of research. Since the publication of the first edition, Biostatistics and Epidemiology has attracted loyal readers from across specialty areas in the biomedical community. The Fifth Edition includes coverage of fixed and random effects and mixed effects models; Poisson regression; constructing confidence intervals for U-shaped relationships; analysis of rare variants; Mendelian randomization; and aspects of machine learning and big data analytics. Biostatistics and Epidemiology was written to be accessible for readers without backgrounds in mathematics. It provides clear explanations of underlying principles, as well as practical guidelines of "how to do it" and "how to interpret it." Key features include a philosophical and logical explanation at the beginning of the book, subsections that can stand alone or serve as reference, cross-referencing, recommended reading, and appendices covering sample calculations for various statistics in the text.
Reviews