Modeling Dose-Response Microarray Data in Early Drug Development Experiments Using R

A wicked way to get started in the weird and wonderful world of electricity! Have some inspired electrical fun with these simple experiments using all kinds of household equipment. Set up a cool circu

Introduction to Statistics Using R is organized into 13 major chapters.Each chapter is broken down into many digestible subsections in order to explore the objectives of the book. There are many real-

Learn how to perform magic tricks and illusions using simple science experiments in this children's activity book for kids aged 7-9. Join science presenter Steve Mould, #1 bestselling author of How to

Large-scale data analytics using machine learning (ML) underpins many modern data-driven applications. ML systems provide means of specifying and executing these ML workloads in an efficient and scala

The primary data driver behind US drug policy is the National Survey on Drug Use and Health. This insider history traces the evolution of the survey and how the survey has interacted with the political and social climate of the country, from its origins during the Vietnam War to its role in the war on drugs. The book includes first-hand accounts that explain how the data was used and misused by political leaders, why changes were made in the survey design, and what challenges researchers faced in communicating statistical principles to policymakers and leaders. It also makes recommendations for managing survey data collection and reporting in the context of political pressures and technological advances. Survey research students and practitioners will learn practical lessons about questionnaire design, mode effects, sampling, nonresponse, weighting, editing, imputation, statistical significance, and confidentiality. The book also includes common-language explanations of key terms and p

Child Development: Early Stages Through Age 12 explores the many stages of growth and development that children experience from the prenatal stage through the school-age years. Through an in-dept

While there are numerous books on the analysis of Generalized Linear Models (GLMs), there is very little information available on how to design the experiments that will collect the data. This book wi

Velazquez. Poussin. Carvaggio. Bernini. Despite their disparate backgrounds, these greats of European Baroque art converged at one remarkable place in time: Rome, 1630. In response to the Protestant R

This book presents different data collection and representation techniques: elementary descriptive statistics, confirmatory statistics, multivariate approaches and statistical modeling. It exposes the

This book presents the statistical analysis of compositional data using the log-ratio approach. It includes a wide range of classical and robust statistical methods adapted for compositional data anal

This book helps students and scholars get started on the exciting journey of using visual data in social research. It covers the many uses a researcher can make of images, from creating images as a pa

Pharmacoepidemiology and Pharmacovigilance: Synergistic Tools to Better Investigate Drug Safety examines the role of pharmacoepidemiologic studies in drug development and its use as a prevention tool

This book is a timely response to a rather urgent call to seek an updated methodology in rereading and reappraising early Chinese texts in light of newly discovered early writings. For a long time, th

This book provides a new analytical approach for dynamic data repeatedly measured from multiple subjects over time. Random effects account for differences across subjects. Auto-regression in response

Explore different perspectives and approaches to create more effective visualizations#MakeoverMonday offers inspiration and a giant dose of perspective for those who communicate data. Originally a sma

Create, maintain, and manage a continual cybersecurity incident response program using the practical steps presented in this book. Don't allow your cybersecurity incident responses (IR) to fall short

A comprehensive guide to the theory, methodology, and development for modeling systems of systems Modeling and Managing Interdependent Complex Systems of Systems examines the complexity of, and the ri

This book covers various multiple-criteria decision making (mcdm) methods for modeling and optimization of advanced manufacturing processes (AMPs). Processes such as non-conventional machining, r

Modern scientific computational methods are undergoing a transformative change; big data and statistical learning methods now have the potential to outperform the classical first-principles modeling paradigm. This book bridges this transition, connecting the theory of probability, stochastic processes, functional analysis, numerical analysis, and differential geometry. It describes two classes of computational methods to leverage data for modeling dynamical systems. The first is concerned with data fitting algorithms to estimate parameters in parametric models that are postulated on the basis of physical or dynamical laws. The second is on operator estimation, which uses the data to nonparametrically approximate the operator generated by the transition function of the underlying dynamical systems. This self-contained book is suitable for graduate studies in applied mathematics, statistics, and engineering. Carefully chosen elementary examples with supplementary MATLAB® codes and append

This handbook summarizes the data and techniques for hypofractionation and stereotactic radiation in a clinically-accessible way. Hypofractionated radiation therapy, which consists of larger-dose radi

What matters most in how poverty shapes children’s well-being and development? How can data inform social policy and practice approaches to improving the outcomes for poorer children? Using life cours

Emerging Spatial Big Data (SBD) has transformative potential in solving many grand societal challenges such as water resource management, food security, disaster response, and transportation. However,

Multiphysics Modeling: Materials, Components, and Systems focuses on situations where coupled phenomena like thermal, flow and mechanics occur. Important fundamentals of the various physics that are r

This book is a comprehensive guide to qualitative comparative analysis (QCA) using R. Using Boolean algebra to implement principles of comparison used by scholars engaged in the qualitative study of

This book provides an in-depth understanding of big data challenges to digital forensic investigations, also known as big digital forensic data. It also develops the basis of using data mining in big

The book presents the basic principles of sound graphical design and applies these principles to engaging examples using the graphical functions available in R. It offers a wide variety of graphical d

This detailed book provides a compilation of laboratory techniques and tests to assess the risks to embryo-fetal development from drug exposure during early developmental stages. After an introduction

Big Data Systems encompass massive challenges related to data diversity, storage mechanisms, and requirements of massive computational power. Further, capabilities of big data systems also vary with r

In this book, Li Min proposes a new paradigm for the foundation and emergence of the classical tradition in early China, from the late Neolithic through the Zhou period. Using a wide range of historical and archaeological data, he explains the development of ritual authority and particular concepts of kingship over time in relation to social memory. His volume weaves together the major benchmarks in the emergence of the classical tradition, particularly how legacies of prehistoric interregional interactions, state formation, urban florescence and collapse during the late third and the second millenniums BCE laid the critical foundation for the Sandai notion of history among Zhou elite. Moreover, the literary-historical accounts of the legendary Xia Dynasty in early China reveal a cultural construction involving social memories of the past and subsequent political elaborations in various phases of history. This volume enables a new understanding on the long-term processes that enabled a

This book provides new theories, applications and quantitative methods in demography, population studies and statistics. It presents and applies data analysis, statistics and stochastic modeling techn

This textbook teaches the fundamentals of building energy modeling and analysis using open source example applications built with the US DOE’s OpenStudio modeling platform and EnergyPlus simulation en

This book offers new transparent views and step-by-step methods for performance evaluation of a set of units using Data Envelopment Analysis (DEA). The book has twelve practical chapters. Elementary c

This book provides an in-depth understanding of big data challenges to digital forensic investigations, also known as big digital forensic data. It also develops the basis of using data mining in big

Covers the latest developments in modeling elastohydrodynamic lubrication (EHL) problems using the finite element method (FEM) This comprehensive guide introduces readers to a powerful technology bein

Learn how to build efficient, secure and robust code in C++ by using data structures and algorithms - the building blocks of C++Key FeaturesUse data structures such as arrays, stacks, trees, lists, an

Cellular trafficking is only recently identified as a site for therapeutic intervention. This book provides up to date information on the mechanism for exploiting this area for drug development as wel

"This textbook will introduce exploratory data analysis (EDA) and will cover the range of interesting features we can expect to find in data. The book will also explore the practical mechanics of usin

Using Applied Econometrics with SAS: Modeling Demand, Supply, and Risk, you will quickly master SAS applications for implementing and estimating standard models in the field of econometrics. This guid

Get started using Python in data analysis with this compact practical guide. This book includes three exercises and a case study on getting data in and out of Python code in the right format. Learn Da

Advances in nonlinear dynamics, especially modern multifractal cascade models, allow us to investigate the weather and climate at unprecedented levels of accuracy. Using new stochastic modeling and data analysis techniques, this book provides an overview of the nonclassical, multifractal statistics. By generalizing the classical turbulence laws, emergent higher-level laws of atmospheric dynamics are obtained and are empirically validated over time-scales of seconds to decades and length-scales of millimetres to the size of the planet. In generalizing the notion of scale, atmospheric complexity is reduced to a manageable scale-invariant hierarchy of processes, thus providing a new perspective for modeling and understanding the atmosphere. This synthesis of state-of-the-art data and nonlinear dynamics is systematically compared with other analyses and global circulation model outputs. This is an important resource for atmospheric science researchers new to multifractal theory and is also