Author: SUSAN. HUBER HOLMES (WOLFGANG.)Publisher: Cambridge University Press
ISBN: 1108427022
Category : Biometry
Languages : en
Pages : 407
Book Description
Modern Statistics for the Life Sciences
Author: Alan GrafenPublisher: Oxford University Press
ISBN: 0199252319
Category : Mathematics
Languages : en
Pages : 368
Book Description
Model formulae represent a powerful methodology for describing, discussing, understanding, and performing that large part of statistical tests known as linear statistics. The book aims to put this methodology firmly within the grasp of undergraduates.
The Fundamentals of Modern Statistical Genetics
Author: Nan M. LairdPublisher: Springer Science & Business Media
ISBN: 1441973389
Category : Medical
Languages : en
Pages : 226
Book Description
This book covers the statistical models and methods that are used to understand human genetics, following the historical and recent developments of human genetics. Starting with Mendel’s first experiments to genome-wide association studies, the book describes how genetic information can be incorporated into statistical models to discover disease genes. All commonly used approaches in statistical genetics (e.g. aggregation analysis, segregation, linkage analysis, etc), are used, but the focus of the book is modern approaches to association analysis. Numerous examples illustrate key points throughout the text, both of Mendelian and complex genetic disorders. The intended audience is statisticians, biostatisticians, epidemiologists and quantitatively- oriented geneticists and health scientists wanting to learn about statistical methods for genetic analysis, whether to better analyze genetic data, or to pursue research in methodology. A background in intermediate level statistical methods is required. The authors include few mathematical derivations, and the exercises provide problems for students with a broad range of skill levels. No background in genetics is assumed.
Modern Issues and Methods in Biostatistics
Author: Mark ChangPublisher: Springer Science & Business Media
ISBN: 144199842X
Category : Medical
Languages : en
Pages : 316
Book Description
Classic biostatistics, a branch of statistical science, has as its main focus the applications of statistics in public health, the life sciences, and the pharmaceutical industry. Modern biostatistics, beyond just a simple application of statistics, is a confluence of statistics and knowledge of multiple intertwined fields. The application demands, the advancements in computer technology, and the rapid growth of life science data (e.g., genomics data) have promoted the formation of modern biostatistics. There are at least three characteristics of modern biostatistics: (1) in-depth engagement in the application fields that require penetration of knowledge across several fields, (2) high-level complexity of data because they are longitudinal, incomplete, or latent because they are heterogeneous due to a mixture of data or experiment types, because of high-dimensionality, which may make meaningful reduction impossible, or because of extremely small or large size; and (3) dynamics, the speed of development in methodology and analyses, has to match the fast growth of data with a constantly changing face. This book is written for researchers, biostatisticians/statisticians, and scientists who are interested in quantitative analyses. The goal is to introduce modern methods in biostatistics and help researchers and students quickly grasp key concepts and methods. Many methods can solve the same problem and many problems can be solved by the same method, which becomes apparent when those topics are discussed in this single volume.
Algebraic and Discrete Mathematical Methods for Modern Biology
Author: Raina RobevaPublisher: Academic Press
ISBN: 0128012714
Category : Mathematics
Languages : en
Pages : 383
Book Description
Written by experts in both mathematics and biology, Algebraic and Discrete Mathematical Methods for Modern Biology offers a bridge between math and biology, providing a framework for simulating, analyzing, predicting, and modulating the behavior of complex biological systems. Each chapter begins with a question from modern biology, followed by the description of certain mathematical methods and theory appropriate in the search of answers. Every topic provides a fast-track pathway through the problem by presenting the biological foundation, covering the relevant mathematical theory, and highlighting connections between them. Many of the projects and exercises embedded in each chapter utilize specialized software, providing students with much-needed familiarity and experience with computing applications, critical components of the "modern biology" skill set. This book is appropriate for mathematics courses such as finite mathematics, discrete structures, linear algebra, abstract/modern algebra, graph theory, probability, bioinformatics, statistics, biostatistics, and modeling, as well as for biology courses such as genetics, cell and molecular biology, biochemistry, ecology, and evolution. - Examines significant questions in modern biology and their mathematical treatments - Presents important mathematical concepts and tools in the context of essential biology - Features material of interest to students in both mathematics and biology - Presents chapters in modular format so coverage need not follow the Table of Contents - Introduces projects appropriate for undergraduate research - Utilizes freely accessible software for visualization, simulation, and analysis in modern biology - Requires no calculus as a prerequisite - Provides a complete Solutions Manual - Features a companion website with supplementary resources
Introduction to Statistics for Biology
Author: Trudy A. WattPublisher: CRC Press
ISBN: 1420011529
Category : Mathematics
Languages : en
Pages : 298
Book Description
Even though an understanding of experimental design and statistics is central to modern biology, undergraduate and graduate students studying biological subjects often lack confidence in their numerical abilities. Allaying the anxieties of students, Introduction to Statistics for Biology, Third Edition provides a painless introduction to the subject while demonstrating the importance of statistics in contemporary biological studies. New to the Third Edition More detailed explanation of the ideas of elementary probability to simplify the rationale behind hypothesis testing, before moving on to simple tests An emphasis on experimental design and data simulation prior to performing an experiment A general template for carrying out statistical tests from hypothesis to interpretation Worked examples and updated Minitab analyses and graphics Downloadable resources contains a free trial version of Minitab Using Minitab throughout to present practical examples, the authors emphasize the interpretation of computer output. With its nontechnical approach and practical advice, this student-friendly introductory text lays the foundation for the advanced study of statistical analysis.
A Modern Introduction to Probability and Statistics
Author: F.M. DekkingPublisher: Springer Science & Business Media
ISBN: 1846281687
Category : Mathematics
Languages : en
Pages : 485
Book Description
Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books
Likelihood Methods in Biology and Ecology
Author: Michael BrimacombePublisher: CRC Press
ISBN: 0429533233
Category : Mathematics
Languages : en
Pages : 274
Book Description
This book emphasizes the importance of the likelihood function in statistical theory and applications and discusses it in the context of biology and ecology. Bayesian and frequentist methods both use the likelihood function and provide differing but related insights. This is examined here both through review of basic methodology and also the integr
An Introduction to Statistical Genetic Data Analysis
Author: Melinda C. MillsPublisher: MIT Press
ISBN: 0262357445
Category : Science
Languages : en
Pages : 433
Book Description
A comprehensive introduction to modern applied statistical genetic data analysis, accessible to those without a background in molecular biology or genetics. Human genetic research is now relevant beyond biology, epidemiology, and the medical sciences, with applications in such fields as psychology, psychiatry, statistics, demography, sociology, and economics. With advances in computing power, the availability of data, and new techniques, it is now possible to integrate large-scale molecular genetic information into research across a broad range of topics. This book offers the first comprehensive introduction to modern applied statistical genetic data analysis that covers theory, data preparation, and analysis of molecular genetic data, with hands-on computer exercises. It is accessible to students and researchers in any empirically oriented medical, biological, or social science discipline; a background in molecular biology or genetics is not required. The book first provides foundations for statistical genetic data analysis, including a survey of fundamental concepts, primers on statistics and human evolution, and an introduction to polygenic scores. It then covers the practicalities of working with genetic data, discussing such topics as analytical challenges and data management. Finally, the book presents applications and advanced topics, including polygenic score and gene-environment interaction applications, Mendelian Randomization and instrumental variables, and ethical issues. The software and data used in the book are freely available and can be found on the book's website.
The Analysis of Biological Data
Author: Michael C. WhitlockPublisher: Macmillan Higher Education
ISBN: 1319226299
Category : Mathematics
Languages : en
Pages : 2074
Book Description
The Analysis of Biological Data provides students with a practical foundation of statistics for biology students. Every chapter has several biological or medical examples of key concepts, and each example is prefaced by a substantial description of the biological setting. The emphasis on real and interesting examples carries into the problem sets where students have dozens of practice problems based on real data. The third edition features over 200 new examples and problems. These include new calculation practice problems, which guide the student step by step through the methods, and a greater number of examples and topics come from medical and human health research. Every chapter has been carefully edited for even greater clarity and ease of use. All the data sets, R scripts for all worked examples in the book, as well as many other teaching resources, are available to qualified instructors (see below).
