Details
Biostatistics for Human Genetic Epidemiology
Advances in Experimental Medicine and Biology, Band 1082
|
213,99 € |
|
| Verlag: | Springer |
| Format: | |
| Veröffentl.: | 24.10.2018 |
| ISBN/EAN: | 9783319937915 |
| Sprache: | englisch |
Dieses eBook enthält ein Wasserzeichen.
Beschreibungen
<p></p><p><b>The book illustrates how biostatistics may numerically summarize human genetic epidemiology using R</b>, and may be used successfully to solve<br></p>
<p><b>problems in quantitative Genetic Epidemiology</b></p>
<p><b> </b></p>
<p><b>Biostatistics for Human Genetic Epidemiology </b>provides </p>
<p>statistical methodologies and R recipes for human genetic </p>
<p>epidemiologic problems. It begins by introducing all the </p>
<p>necessary probabilistic and statistical foundations, before </p>
moving on to topics related human genetic epidemiology, <p></p>
<p>with R codes illustrations for various examples.</p>
<p> </p>
<p>This clear and concise book covers human genetic </p>
<p>epidemiology, using R in data analysis, including multivariate</p>
<p>data analysis. It examines probabilistic and statistical theories </p>
<p>for modeling human genetic epidemiology – leading the readers </p>
through an effective epidemiologic model, from simple to<p></p>
<p>advanced levels. Classical mathematical, probabilistic, and </p>
<p>statistical theory are thoroughly discussed and presented. This </p>
book also presents R as a calculator and using R in data analysis.<p></p>
<p>Additionally, it covers Advanced Human Genetic Data </p>
Concepts, the Study of Human Genetic Variation, Manhattan <p></p>
<p>Plots, as well as the Procedures for Multiple Comparison. </p>
<p>Numerous <i>Worked Examples</i> are provided for illustrations of </p>
<p>concepts and real-life applications.</p>
<p><b><i> </i></b></p>
<p><b><i>Biostatistics for Human Genetic Epidemiology </i></b>is an ideal </p>
<p>reference for professionals and students in Medicine </p>
<p>(particularly in Preventive Medicine and Public Health </p>
Medical Practices), as well as in Genetics, Epidemiology, and <p></p>
<p>Biostatistics.</p><br><p></p>
<p><b>problems in quantitative Genetic Epidemiology</b></p>
<p><b> </b></p>
<p><b>Biostatistics for Human Genetic Epidemiology </b>provides </p>
<p>statistical methodologies and R recipes for human genetic </p>
<p>epidemiologic problems. It begins by introducing all the </p>
<p>necessary probabilistic and statistical foundations, before </p>
moving on to topics related human genetic epidemiology, <p></p>
<p>with R codes illustrations for various examples.</p>
<p> </p>
<p>This clear and concise book covers human genetic </p>
<p>epidemiology, using R in data analysis, including multivariate</p>
<p>data analysis. It examines probabilistic and statistical theories </p>
<p>for modeling human genetic epidemiology – leading the readers </p>
through an effective epidemiologic model, from simple to<p></p>
<p>advanced levels. Classical mathematical, probabilistic, and </p>
<p>statistical theory are thoroughly discussed and presented. This </p>
book also presents R as a calculator and using R in data analysis.<p></p>
<p>Additionally, it covers Advanced Human Genetic Data </p>
Concepts, the Study of Human Genetic Variation, Manhattan <p></p>
<p>Plots, as well as the Procedures for Multiple Comparison. </p>
<p>Numerous <i>Worked Examples</i> are provided for illustrations of </p>
<p>concepts and real-life applications.</p>
<p><b><i> </i></b></p>
<p><b><i>Biostatistics for Human Genetic Epidemiology </i></b>is an ideal </p>
<p>reference for professionals and students in Medicine </p>
<p>(particularly in Preventive Medicine and Public Health </p>
Medical Practices), as well as in Genetics, Epidemiology, and <p></p>
<p>Biostatistics.</p><br><p></p>
<p></p><p>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.</p><p></p>
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.
<b>This book illustrates how biostatistics may numerically summaries</b><p><b>human genetic </b>R<b>, and may be used successfully to solve</b></p><p><b>problems in quantitative Genetic Epidemiology</b></p><p><b> </b></p><p><b><i>Biostatistics for Human Genetic Epidemiology </i></b>provides</p><p>statistical methodologies and R recipes for human genetic</p><p>epidemiologic problems. It begins by introducing all the</p><p>necessary probabilistic and statistical foundations, before</p><p>moving on to topics related human genetic epidemiology,</p>with R codes illustrations for various examples.<p></p><p> </p><p>This clear and concise book covers human genetic</p>epidemiology, using R in data analysis, including multivariate<p></p><p>data analysis. It examines probabilistic and statistical theories</p><p>for modeling human genetic epidemiology – leading the readers</p><p>through an effective epidemiologic model, from simple to</p><p>advanced levels. Classical mathematical, probabilistic, and</p><p>statistical theory are thoroughly discussed and presented. This</p><p>book also presents R as a calculator and using R in data analysis.</p><p>Additionally, it covers Advanced Human Genetic Data</p><p>Concepts, the Study of Human Genetic Variation, Manhattan</p>Plots, as well as the Procedures for Multiple Comparison. <p></p><p>Numerous <i>Worked Examples</i> are provided for illustrations of</p><p>concepts and real-life applications.</p><p><b><i> </i></b></p><p><b><i>Biostatistics for Human Genetic Epidemiology </i></b>is an ideal</p><p>reference for professionals and students in Medicine</p>(particularly in Preventive Medicine and Public Health<p></p><p>Medical Practices), as well as in Genetics, Epidemiology, and</p><p>Biostatistics.</p><div><br></div>
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
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