chan bertram (15 Ergebnisse)

XVI, 355 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Advances in Experimental Medicine and Biology. Volume 1082. Sprache: Englisch.

Zustand: New. pp. 448.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. Bertram K. C. Chan, PhD, is Consulting Biostatistician at the Loma Linda University Health, School of Medicine, Loma Linda, CA. Dr. Chan is also Software Development and Forum Lecturer at the School of Public Health, LLUH Department of Biostatistics and Epi.

Kartoniert / Broschiert. Zustand: New. Since it first appeared in 1996, the open-source programming language R has become increasingly popular as an environment for statistical analysis and graphical output. This is the first textbook to present classical biostatistical analysis for epidemiology.

Paperback. Zustand: Brand New. 1st edition. 446 pages. 10.00x7.00x1.00 inches. In Stock.

Hardcover. Zustand: Brand New. har/psc edition. 514 pages. 9.00x6.00x1.00 inches. In Stock.

Zustand: New. 2017. 1st Edition. Hardcover. . . . . . Books ship from the US and Ireland.

Zustand: New. BERTRAM K. C. CHAN, PhD, is Consulting Biostatistician at the Loma Linda University Health, School of Medicine, Loma Linda, CA. Dr. Chan is also Software Development and Forum Lecturer at the School of Public Health, LLUH Department of Biostatistics and Epi.

Buch. Zustand: Neu. Neuware - Illustrates how R may be used successfully to solve problems in quantitative financeApplied Probabilistic Calculus for Financial Engineering: An Introduction Using R provides R recipes for asset allocation and portfolio optimization problems. It begins by introducing all the necessary probabilistic and statistical foundations, before moving on to topics related to asset allocation and portfolio optimization with R codes illustrated for various examples. This clear and concise book covers financial engineering, using R in data analysis, and univariate, bivariate, and multivariate data analysis. It examines probabilistic calculus for modeling financial engineering--walking the reader through building an effective financial model from the Geometric Brownian Motion (GBM) Model via probabilistic calculus, while also covering Ito Calculus. Classical mathematical models in financial engineering and modern portfolio theory are discussed--along with the Two Mutual Fund Theorem and The Sharpe Ratio. The book also looks at R as a calculator and using R in data analysis in financial engineering. Additionally, it covers asset allocation using R, financial risk modeling and portfolio optimization using R, global and local optimal values, locating functional maxima and minima, and portfolio optimization by performance analytics in CRAN.\* Covers optimization methodologies in probabilistic calculus for financial engineering\* Answers the question: What does a 'Random Walk' Financial Theory look like \* Covers the GBM Model and the Random Walk Model\* Examines modern theories of portfolio optimization, including The Markowitz Model of Modern Portfolio Theory (MPT), The Black-Litterman Model, and The Black-Scholes Option Pricing ModelApplied Probabilistic Calculus for Financial Engineering: An Introduction Using R s an ideal reference for professionals and students in economics, econometrics, and finance, as well as for financial investment quants and financial engineers.

Taschenbuch. Zustand: Neu. Neuware - Since it first appeared in 1996, the open-source programming language R has become increasingly popular as an environment for statistical analysis and graphical output. This is the first textbook to present classical biostatistical analysis for epidemiology and related public health sciences to students using the R language.

Buch. Zustand: Neu. Neuware -The book illustrates how biostatistics may numerically summarize human genetic epidemiology using R, and may be used successfully to solveproblems in quantitative Genetic EpidemiologyBiostatistics for Human Genetic Epidemiology providesstatistical methodologies and R recipes for human geneticepidemiologic problems. It begins by introducing all thenecessary probabilistic and statistical foundations, beforemoving on to topics related human genetic epidemiologywith R codes illustrations for various examples.This clear and concise book covers human geneticepidemiology, using R in data analysis, including multivariatedata analysis. It examines probabilistic and statistical theoriesfor modeling human genetic epidemiology ¿ leading the readersthrough an effective epidemiologic model, from simple toadvanced levels. Classical mathematical, probabilistic, andstatistical theory are thoroughly discussed and presented. Thisbook also presents R as a calculator and using R in data analysis.Additionally, it covers Advanced Human Genetic DataConcepts, the Study of Human Genetic Variation, ManhattanPlots, as well as the Procedures for Multiple Comparison.Numerous Worked Examples are provided for illustrations ofconcepts and real-life applications.Biostatistics for Human Genetic Epidemiology is an idealreference for professionals and students in Medicine(particularly in Preventive Medicine and Public HealthMedical Practices), as well as in Genetics, Epidemiology, andBiostatistics.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 372 pp. Englisch.

Taschenbuch. Zustand: Neu. Neuware -The book illustrates how biostatistics may numerically summarize human genetic epidemiology using R, and may be used successfully to solveproblems in quantitative Genetic EpidemiologyBiostatistics for Human Genetic Epidemiology providesstatistical methodologies and R recipes for human geneticepidemiologic problems. It begins by introducing all thenecessary probabilistic and statistical foundations, beforemoving on to topics related human genetic epidemiologywith R codes illustrations for various examples.This clear and concise book covers human geneticepidemiology, using R in data analysis, including multivariatedata analysis. It examines probabilistic and statistical theoriesfor modeling human genetic epidemiology ¿ leading the readersthrough an effective epidemiologic model, from simple toadvanced levels. Classical mathematical, probabilistic, andstatistical theory are thoroughly discussed and presented. Thisbook also presents R as a calculator and using R in data analysis.Additionally, it covers Advanced Human Genetic DataConcepts, the Study of Human Genetic Variation, ManhattanPlots, as well as the Procedures for Multiple Comparison.Numerous Worked Examples are provided for illustrations ofconcepts and real-life applications.Biostatistics for Human Genetic Epidemiology is an idealreference for professionals and students in Medicine(particularly in Preventive Medicine and Public HealthMedical Practices), as well as in Genetics, Epidemiology, andBiostatistics.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 372 pp. Englisch.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The book illustrates how biostatistics may numerically summarize human genetic epidemiology using R, and may be used successfully to solveproblems in quantitative Genetic EpidemiologyBiostatistics 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 multivariatedata analysis. It examines probabilistic and statistical theories for modeling human genetic epidemiology - leading the readers through an effective epidemiologic model, from simple toadvanced 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.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The book illustrates how biostatistics may numerically summarize human genetic epidemiology using R, and may be used successfully to solveproblems in quantitative Genetic EpidemiologyBiostatistics 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 multivariatedata analysis. It examines probabilistic and statistical theories for modeling human genetic epidemiology - leading the readers through an effective epidemiologic model, from simple toadvanced 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.