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Biostatistics for Human Genetic Epidemiology: Advances in Experimental Medicine and Biology, cartea 1082

Autor Bertram K. C. Chan
en Limba Engleză Hardback – 3 noi 2018
The book illustrates how biostatistics may numerically summarize human genetic epidemiology using R, and may be used successfully to solve

problems in quantitative Genetic Epidemiology
 
Biostatistics for Human Genetic Epidemiology provides
statistical methodologies and R recipes for human genetic
epidemiologic problems.  It begins by introducing all the
necessary probabilistic and statistical foundations, before
moving on to topics related human genetic epidemiology, with R codes illustrations for various examples.
 
This clear and concise book covers human genetic
epidemiology, using R in data analysis, including multivariate
data analysis.  It examines probabilistic and statistical theories
for modeling human genetic epidemiology – leading the readers
through an effective epidemiologic model, from simple to advanced levels.  Classical mathematical, probabilistic, and
statistical theory are thoroughly discussed and presented.  This
book also presents R as a calculator and using R in data analysis. Additionally, it covers Advanced Human Genetic Data
Concepts, the Study of Human Genetic Variation, Manhattan Plots, as well as the Procedures for Multiple Comparison.  
Numerous Worked Examples are provided for illustrations of
concepts and real-life applications.
 
Biostatistics for Human Genetic Epidemiology is an ideal
reference for professionals and students in Medicine
(particularly in Preventive Medicine and Public Health
Medical Practices), as well as in Genetics, Epidemiology, and Biostatistics.

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Specificații

ISBN-13: 9783319937908
ISBN-10: 3319937901
Pagini: 392
Ilustrații: XVI, 355 p. 85 illus., 44 illus. in color.
Dimensiuni: 178 x 254 x 27 mm
Greutate: 0.91 kg
Ediția:1st ed. 2018
Editura: Springer International Publishing
Colecția Springer
Seria Advances in Experimental Medicine and Biology

Locul publicării:Cham, Switzerland

Cuprins

Preface.- Dedication.- Contents.- Introduction To Human Genetic Epidemiology.- Data Analysis Using R Programming.- Applied Statistics For Human Genetics Using R.-  Applied Human Genetic Epidemiology.- Human Genetic Epidemiology Using R.- References.- Subject Index.

Notă biografică

Dr. Bertram K. C. Chan is a Lecturer at the Loma Linda University of Health in the Deparment of Epidemiology and Biostatistics. He has extensive knowledge is this field and has experience writing on this subject.

Textul de pe ultima copertă

This book illustrates how biostatistics may numerically summarieshuman genetic R, and may be used successfully to solve
problems in quantitative Genetic Epidemiology
 
Biostatistics for Human Genetic Epidemiology provides
statistical methodologies and R recipes for human genetic
epidemiologic problems.  It begins by introducing all the
necessary probabilistic and statistical foundations, before
moving on to topics related human genetic epidemiology,
with R codes illustrations for various examples.  
This clear and concise book covers human genetic
epidemiology, using R in data analysis, including multivariate data analysis.  It examines probabilistic and statistical theories
for modeling human genetic epidemiology – leading the readers
through an effective epidemiologic model, from simple to
advanced levels.  Classical mathematical, probabilistic, and
statistical theory are thoroughly discussed and presented.  This
book also presents R as a calculator and using R in data analysis.
Additionally, it covers Advanced Human Genetic Data
Concepts, the Study of Human Genetic Variation, Manhattan
Plots, as well as the Procedures for Multiple Comparison.   Numerous Worked Examples are provided for illustrations of
concepts and real-life applications.
 
Biostatistics for Human Genetic Epidemiology is an ideal
reference for professionals and students in Medicine
(particularly in Preventive Medicine and Public Health Medical Practices), as well as in Genetics, Epidemiology, and
Biostatistics.


Caracteristici

Correlates with modern genetics in medicine Provides a current working knowledge of genetic epidemiology Describes statistical methods for quantitative assessment of genetic influences on diseases Focuses on research study designs for discovering disease susceptibility genes Introduces the use of the popular open-sourced computer programming language, R, for needed quantitative assessment in epidemiologic analysis