Modern Statistics for Modern Biology
Author: SUSAN. HUBER HOLMES (WOLFGANG.)
Publisher: Cambridge University Press
Published: 2018
Total Pages: 407
ISBN-13: 1108427022
DOWNLOAD EBOOK →Lanterna Rally
eBook PDF Download Digital Library
Modern Statistics for the Life Sciences
Author: Alan Grafen
Publisher: Oxford University Press
Published: 2002-03-21
Total Pages: 368
ISBN-13: 0199252319
DOWNLOAD EBOOK →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. Laird
Publisher: Springer Science & Business Media
Published: 2010-12-13
Total Pages: 226
ISBN-13: 1441973389
DOWNLOAD EBOOK →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 Statistics for Modern Biology
Author: Susan Holmes
Publisher:
Published: 2019
Total Pages: 382
ISBN-13: 9781108551441
DOWNLOAD EBOOK →Introduction to Statistics for Biology
Author: Trudy A. Watt
Publisher: CRC Press
Published: 2007-05-17
Total Pages: 298
ISBN-13: 1420011529
DOWNLOAD EBOOK →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. Dekking
Publisher: Springer Science & Business Media
Published: 2006-03-30
Total Pages: 488
ISBN-13: 1846281687
DOWNLOAD EBOOK →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
Modern Statistics with R
Author: Måns Thulin
Publisher: BoD - Books on Demand
Published: 2021-07-28
Total Pages: 598
ISBN-13: 9152701514
DOWNLOAD EBOOK →The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. The aim of Modern Statistics with R is to introduce you to key parts of the modern statistical toolkit. It teaches you: - Data wrangling - importing, formatting, reshaping, merging, and filtering data in R. - Exploratory data analysis - using visualisation and multivariate techniques to explore datasets. - Statistical inference - modern methods for testing hypotheses and computing confidence intervals. - Predictive modelling - regression models and machine learning methods for prediction, classification, and forecasting. - Simulation - using simulation techniques for sample size computations and evaluations of statistical methods. - Ethics in statistics - ethical issues and good statistical practice. - R programming - writing code that is fast, readable, and free from bugs. Starting from the very basics, Modern Statistics with R helps you learn R by working with R. Topics covered range from plotting data and writing simple R code to using cross-validation for evaluating complex predictive models and using simulation for sample size determination. The book includes more than 200 exercises with fully worked solutions. Some familiarity with basic statistical concepts, such as linear regression, is assumed. No previous programming experience is needed.
Data Analysis for the Life Sciences with R
Author: Rafael A. Irizarry
Publisher: CRC Press
Published: 2016-10-04
Total Pages: 461
ISBN-13: 1498775861
DOWNLOAD EBOOK →This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained.
Bernoulli's Fallacy
Author: Aubrey Clayton
Publisher: Columbia University Press
Published: 2021-08-03
Total Pages: 641
ISBN-13: 0231553358
DOWNLOAD EBOOK →There is a logical flaw in the statistical methods used across experimental science. This fault is not a minor academic quibble: it underlies a reproducibility crisis now threatening entire disciplines. In an increasingly statistics-reliant society, this same deeply rooted error shapes decisions in medicine, law, and public policy with profound consequences. The foundation of the problem is a misunderstanding of probability and its role in making inferences from observations. Aubrey Clayton traces the history of how statistics went astray, beginning with the groundbreaking work of the seventeenth-century mathematician Jacob Bernoulli and winding through gambling, astronomy, and genetics. Clayton recounts the feuds among rival schools of statistics, exploring the surprisingly human problems that gave rise to the discipline and the all-too-human shortcomings that derailed it. He highlights how influential nineteenth- and twentieth-century figures developed a statistical methodology they claimed was purely objective in order to silence critics of their political agendas, including eugenics. Clayton provides a clear account of the mathematics and logic of probability, conveying complex concepts accessibly for readers interested in the statistical methods that frame our understanding of the world. He contends that we need to take a Bayesian approach—that is, to incorporate prior knowledge when reasoning with incomplete information—in order to resolve the crisis. Ranging across math, philosophy, and culture, Bernoulli’s Fallacy explains why something has gone wrong with how we use data—and how to fix it.
Algebraic and Discrete Mathematical Methods for Modern Biology
Author: Raina Robeva
Publisher: Academic Press
Published: 2015-05-09
Total Pages: 382
ISBN-13: 0128012714
DOWNLOAD EBOOK →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
