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Exploration and Analysis of DNA Microarray and Other High-Dimensional Data
by Dhammika Amaratunga Ziv Shkedy Javier CabreraExploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition provides comprehensive coverage of recent advancements in microarray data analysis. A cutting-edge guide, the Second Edition demonstrates various methodologies for analyzing data in biomedical research and offers an overview of the modern techniques used in microarray technology to study patterns of gene activity. The new edition answers the need for an efficient outline of all phases of this revolutionary analytical technique, from preprocessing to the analysis stage. Utilizing research and experience from highly-qualified authors in fields of data analysis, Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition features: A new chapter on the interpretation of findings that includes a discussion of signatures and material on gene set analysis, including network analysisNew topics of coverage including ABC clustering, biclustering, partial least squares, penalized methods, ensemble methods, and enriched ensemble methodsUpdated exercises to deepen knowledge of the presented material and provide readers with resources for further study The book is an ideal reference for scientists in biomedical and genomics research fields who analyze DNA microarrays and protein array data, as well as statisticians and bioinformatics practitioners. Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition is also a useful text for graduate-level courses on statistics, computational biology, and bioinformatics.
Explorations in Complex Functions (Graduate Texts in Mathematics #287)
by Richard Beals Roderick S. WongThis textbook explores a selection of topics in complex analysis. From core material in the mainstream of complex analysis itself, to tools that are widely used in other areas of mathematics, this versatile compilation offers a selection of many different paths. Readers interested in complex analysis will appreciate the unique combination of topics and connections collected in this book. Beginning with a review of the main tools of complex analysis, harmonic analysis, and functional analysis, the authors go on to present multiple different, self-contained avenues to proceed. Chapters on linear fractional transformations, harmonic functions, and elliptic functions offer pathways to hyperbolic geometry, automorphic functions, and an intuitive introduction to the Schwarzian derivative. The gamma, beta, and zeta functions lead into L-functions, while a chapter on entire functions opens pathways to the Riemann hypothesis and Nevanlinna theory. Cauchy transforms give rise to Hilbert and Fourier transforms, with an emphasis on the connection to complex analysis. Valuable additional topics include Riemann surfaces, steepest descent, tauberian theorems, and the Wiener–Hopf method. Showcasing an array of accessible excursions, Explorations in Complex Functions is an ideal companion for graduate students and researchers in analysis and number theory. Instructors will appreciate the many options for constructing a second course in complex analysis that builds on a first course prerequisite; exercises complement the results throughout.
Explorations in Computing: An Introduction to Computer Science (Chapman & Hall/CRC Textbooks in Computing)
by John S. ConeryBased on the author's introductory course at the University of Oregon, Explorations in Computing: An Introduction to Computer Science focuses on the fundamental idea of computation and offers insight into how computation is used to solve a variety of interesting and important real-world problems. Taking an active learning approach, the text encoura
Explorations in Computing: An Introduction to Computer Science and Python Programming (Chapman & Hall/CRC Textbooks in Computing)
by John S. ConeryAn Active Learning Approach to Teaching the Main Ideas in Computing Explorations in Computing: An Introduction to Computer Science and Python Programming teaches computer science students how to use programming skills to explore fundamental concepts and computational approaches to solving problems. Tbook gives beginning students an introduction to
Explorations in Core Math for Common Core Grade 7
by Houghton Mifflin HarcourtNIMAC-sourced textbook
Explorations in Monte Carlo Methods (Undergraduate Texts in Mathematics)
by Ronald W. Shonkwiler Franklin MendivilMonte Carlo Methods are among the most used, and useful, computational tools available today. They provide efficient and practical algorithms to solve a wide range of scientific and engineering problems in dozens of areas many of which are covered in this text. These include simulation, optimization, finance, statistical mechanics, birth and death processes, Bayesian inference, quadrature, gambling systems and more.This text is for students of engineering, science, economics and mathematics who want to learn about Monte Carlo methods but have only a passing acquaintance with probability theory. The probability needed to understand the material is developed within the text itself in a direct manner using Monte Carlo experiments for reinforcement. There is a prerequisite of at least one year of calculus and a semester of matrix algebra.Each new idea is carefully motivated by a realistic problem, thus leading to insights into probability theory via examples and numerical simulations. Programming exercises are integrated throughout the text as the primary vehicle for learning the material. All examples in the text are coded in Python as a representative language; the logic is sufficiently clear so as to be easily translated into any other language. Further, Python scripts for each worked example are freely accessible for each chapter. Along the way, most of the basic theory of probability is developed in order to illuminate the solutions to the questions posed. One of the strongest features of the book is the wealth of completely solved example problems. These provide the reader with a sourcebook to follow towards the solution of their own computational problems. Each chapter ends with a large collection of homework problems illustrating and directing the material. This book is suitable as a textbook for students of engineering, finance, and the sciences as well as mathematics. The problem-oriented approach makes it ideal for an applied course in basic probability as well as for a more specialized course in Monte Carlo Methods. Topics include probability distributions, probability calculations, sampling, counting combinatorial objects, Markov chains, random walks, simulated annealing, genetic algorithms, option pricing, gamblers ruin, statistical mechanics, random number generation, Bayesian Inference, Gibbs Sampling and Monte Carlo integration.
Explorations in the Mathematics of Data Science: The Inaugural Volume of the Center for Approximation and Mathematical Data Analytics (Applied and Numerical Harmonic Analysis)
by Simon Foucart Stephan WojtowytschThis edited volume reports on the recent activities of the new Center for Approximation and Mathematical Data Analytics (CAMDA) at Texas A&M University. Chapters are based on talks from CAMDA’s inaugural conference – held in May 2023 – and its seminar series, as well as work performed by members of the Center. They showcase the interdisciplinary nature of data science, emphasizing its mathematical and theoretical foundations, especially those rooted in approximation theory.
Exploratory and Descriptive Statistics (The SAGE Quantitative Research Kit)
by Julie Scott Jones GoldringNervous about statistics? This guide offers you a clear, straight to the point break down of exploratory and descriptive statistics and its potential. Anchored by lots of examples and exercises to enhance your learning, this book will give you the know-how and confidence needed to succeed on your quantitative research journey.
Exploratory and Descriptive Statistics (The SAGE Quantitative Research Kit)
by Julie Scott Jones GoldringNervous about statistics? This guide offers you a clear, straight to the point break down of exploratory and descriptive statistics and its potential. Anchored by lots of examples and exercises to enhance your learning, this book will give you the know-how and confidence needed to succeed on your quantitative research journey.
Exploratory Data Analysis in Business and Economics
by Thomas CleffIn a world in which we are constantly surrounded by data, figures, and statistics, it is imperative to understand and to be able to use quantitative methods. Statistical models and methods are among the most important tools in economic analysis, decision-making and business planning. This textbook, "Exploratory Data Analysis in Business and Economics", aims to familiarise students of economics and business as well as practitioners in firms with the basic principles, techniques, and applications of descriptive statistics and data analysis. Drawing on practical examples from business settings, it demonstrates the basic descriptive methods of univariate and bivariate analysis. The textbook covers a range of subject matter, from data collection and scaling to the presentation and univariate analysis of quantitative data, and also includes analytic procedures for assessing bivariate relationships. It does not confine itself to presenting descriptive statistics, but also addresses the use of computer programmes such as Excel, SPSS, and STATA, thus treating all of the topics typically covered in a university course on descriptive statistics. The German edition of this textbook is one of the "bestsellers" on the German market for literature in statistics.
Exploratory Data Analysis Using R (Chapman and Hall/CRC Data Mining and Knowledge Discovery Series)
by Ronald K. PearsonExploratory Data Analysis Using R provides a classroom-tested introduction to exploratory data analysis (EDA) and introduces the range of "interesting" – good, bad, and ugly – features that can be found in data, and why it is important to find them. It also introduces the mechanics of using R to explore and explain data. The book begins with a detailed overview of data, exploratory analysis, and R, as well as graphics in R. It then explores working with external data, linear regression models, and crafting data stories. The second part of the book focuses on developing R programs, including good programming practices and examples, working with text data, and general predictive models. The book ends with a chapter on "keeping it all together" that includes managing the R installation, managing files, documenting, and an introduction to reproducible computing. The book is designed for both advanced undergraduate, entry-level graduate students, and working professionals with little to no prior exposure to data analysis, modeling, statistics, or programming. it keeps the treatment relatively non-mathematical, even though data analysis is an inherently mathematical subject. Exercises are included at the end of most chapters, and an instructor's solution manual is available.
Exploratory Data Analysis with MATLAB (Chapman & Hall/CRC Computer Science & Data Analysis)
by Wendy L. Martinez Angel R. Martinez Jeffrey SolkaPraise for the Second Edition:"The authors present an intuitive and easy-to-read book. … accompanied by many examples, proposed exercises, good references, and comprehensive appendices that initiate the reader unfamiliar with MATLAB."—Adolfo Alvarez Pinto, International Statistical Review "Practitioners of EDA who use MATLAB will want a copy of this book. … The authors have done a great service by bringing together so many EDA routines, but their main accomplishment in this dynamic text is providing the understanding and tools to do EDA. —David A Huckaby, MAA Reviews Exploratory Data Analysis (EDA) is an important part of the data analysis process. The methods presented in this text are ones that should be in the toolkit of every data scientist. As computational sophistication has increased and data sets have grown in size and complexity, EDA has become an even more important process for visualizing and summarizing data before making assumptions to generate hypotheses and models. Exploratory Data Analysis with MATLAB, Third Edition presents EDA methods from a computational perspective and uses numerous examples and applications to show how the methods are used in practice. The authors use MATLAB code, pseudo-code, and algorithm descriptions to illustrate the concepts. The MATLAB code for examples, data sets, and the EDA Toolbox are available for download on the book’s website. New to the Third Edition Random projections and estimating local intrinsic dimensionality Deep learning autoencoders and stochastic neighbor embedding Minimum spanning tree and additional cluster validity indices Kernel density estimation Plots for visualizing data distributions, such as beanplots and violin plots A chapter on visualizing categorical data
Exploratory Factor Analysis (Quantitative Applications in the Social Sciences #182)
by Holmes FinchA firm knowledge of factor analysis is key to understanding much published research in the social and behavioral sciences. Exploratory Factor Analysis by W. Holmes Finch provides a solid foundation in exploratory factor analysis (EFA), which along with confirmatory factor analysis, represents one of the two major strands in this field. The book lays out the mathematical foundations of EFA; explores the range of methods for extracting the initial factor structure; explains factor rotation; and outlines the methods for determining the number of factors to retain in EFA. The concluding chapter addresses a number of other key issues in EFA, such as determining the appropriate sample size for a given research problem, and the handling of missing data. It also offers brief introductions to exploratory structural equation modeling, and multilevel models for EFA. Example computer code, and the annotated output for all of the examples included in the text are available on an accompanying website.
Exploratory Factor Analysis (Quantitative Applications in the Social Sciences #182)
by Holmes FinchA firm knowledge of factor analysis is key to understanding much published research in the social and behavioral sciences. Exploratory Factor Analysis by W. Holmes Finch provides a solid foundation in exploratory factor analysis (EFA), which along with confirmatory factor analysis, represents one of the two major strands in this field. The book lays out the mathematical foundations of EFA; explores the range of methods for extracting the initial factor structure; explains factor rotation; and outlines the methods for determining the number of factors to retain in EFA. The concluding chapter addresses a number of other key issues in EFA, such as determining the appropriate sample size for a given research problem, and the handling of missing data. It also offers brief introductions to exploratory structural equation modeling, and multilevel models for EFA. Example computer code, and the annotated output for all of the examples included in the text are available on an accompanying website.
Exploratory Multivariate Analysis by Example Using R (Chapman & Hall/CRC Computer Science & Data Analysis)
by Francois Husson Sebastien Le Jérôme PagèsFull of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) a
Explore Business, Technology Opportunities and Challenges After the Covid-19 Pandemic (Lecture Notes in Networks and Systems #495)
by Bahaaeddin Alareeni Allam HamdanThis book constitutes the refereed proceedings of the International Conference on Business and Technology (ICBT2021) organized by EuroMid Academy of Business and Technology (EMABT), held in Istanbul, between November 06–07, 2021. In response to the call for papers for ICBT2021, 485 papers were submitted for presentation and inclusion in the proceedings of the conference. After a careful blind refereeing process, 292 papers were selected for inclusion in the conference proceedings from forty countries. Each of these chapters was evaluated through an editorial board, and each chapter was passed through a double-blind peer-review process. The book highlights a range of topics in the fields of technology, entrepreneurship, business administration, accounting, and economics that can contribute to business development in countries, such as learning machines, artificial intelligence, big data, deep learning, game-based learning, management information system, accounting information system, knowledge management, entrepreneurship and social enterprise, corporate social responsibility and sustainability, business policy and strategic management, international management and organizations, organizational behavior and HRM, operations management and logistics research, controversial issues in management and organizations, turnaround, corporate entrepreneurship, and innovation, legal issues, business ethics, and firm governance, managerial accounting and firm financial affairs, non-traditional research and creative methodologies. These proceedings are reflecting quality research contributing theoretical and practical implications, for those who are wise to apply the technology within any business sector. It is our hope that the contribution of this book proceedings will be of the academic level which even decision-makers in the various economic and executive-level will get to appreciate.
Explorers in North America: Solving Addition and Subtraction Problems Using Timelines
by Kerri O'DonnellThis book introduces basic addition and subtraction problems through the chronological overview of exploration in North America. Includes artifacts such as an excerpt from Champlain's book about his voyage, in addition to an early map of New Amsterdam.
Exploring Arithmetic, Grade 3
by Rod Staff PublishersThis hardcover textbook has 170 lessons. It reviews addition and subtraction skills from Grades 1 and 2 and teaches multiplication and division facts through table 9 and simple two- and three-step multiplication and division. Other concepts drilled are fraction meaning, measure equivalents, money values, and telling time. Mixed computation and Roman numerals are introduced. Mathematics for Christian Living Series
Exploring Blockchain Applications: Management Perspectives
by Sezer Bozkus Kahyaoglu Vahap TecimIn this book, the development process of blockchain algorithms and examples of their applications in different sectors are explored. The opportunities and challenges of blockchain implementations that arise in making technological innovations usable in corporate structures are discussed. In this respect, the book aims to deal with both the conceptual framework and the real challenges and opportunities encountered in practice regarding the blockchain applications. It is tried to contribute to the literature by presenting practical blockchain application suggestions to the readers on a scientific basis.It is a fact that blockchain technology is considered one of the most disruptive and revolutionary innovations after the invention of the internet. Blockchain technology, which was first used for cross-border payments, is coming up with a new application area in a different sector every day. The main purpose of Blockchain-based systems is to spread the "trust" service provided by a central intermediary to machines in transactions between two parties. Thus, it removes the need for this trust from the monopoly of a single intermediary. Blockchain implementation scenarios are to establish math-based trust in an untrusted environment.While exploring the complexity of blockchain applications in different sectors, the emerging risks are also examined from a management perspective. In particular, it is aimed to be a key work that the management levels of the enterprises can benefit from in the decision-making processes.It will be seen that blockchain technologies will be used unlimitedly in design, planning, management and decision making. This book will also introduce new visions for practitioners to use different blockchain technologies and methodologies to face problems.
Exploring Calculus: Labs and Projects with Mathematica (Textbooks in Mathematics)
by Crista Arangala Karen A. YokleyThis text is meant to be a hands-on lab manual that can be used in class every day to guide the exploration of the theory and applications of differential and integral calculus. For the most part, labs can be used individually or in a sequence. Each lab consists of an explanation of material with integrated exercises. Some labs are split into multiple subsections and thus exercises are separated by those subsections. The exercise sections integrate problems, technology, Mathematica R visualization, and Mathematica CDFs that allow students to discover the theory and applications of differential and integral calculus in a meaningful and memorable way.
Exploring Chaos: Theory And Experiment (Studies In Nonlinearity Ser.)
by Brian DaviesThis book presents elements of the theory of chaos in dynamical systems in a framework of theoretical understanding coupled with numerical and graphical experimentation. The theory is developed using only elementary calculus and algebra, and includes dynamics of one-and two-dimensional maps, periodic orbits, stability and its quantification, chaotic behavior, and bifurcation theory of one-dimensional systems. There is an introduction to the theory of fractals, with an emphasis on the importance of scaling, and a concluding chapter on ordinary differential equations. The accompanying software, written in Java, is available online (see link below). The program enables students to carry out their own quantitative experiments on a variety of nonlinear systems, including the analysis of fixed points of compositions of maps, calculation of Fourier spectra and Lyapunov exponents, and box counting for two-dimensional maps. It also provides for visualizing orbits, final state and bifurcation diagrams, Fourier spectra and Lyapunov exponents, basins of attractions, three-dimensional orbits, Poincar?ections, and return maps. Please visit http://www.maths.anu.edu.au/~briand/chaos/ for the integrated cross-platform software.
Exploring Chemical Concepts Through Theory and Computation
by Shubin LiuExploring Chemical Concepts Through Theory and Computation Deep, theoretical resource on the essence of chemistry, explaining a variety of important concepts including redox states and bond types Exploring Chemical Concepts Through Theory and Computation provides a comprehensive account of how the three widely used theoretical frameworks of valence bond theory, molecular orbital theory, and density functional theory, along with a variety of important chemical concepts, can between them describe and efficiently and reliably predict key chemical parameters and phenomena. By comparing the three main theoretical frameworks, readers will become competent in choosing the right modeling approach for their task. The authors go beyond a simple comparison of existing algorithms to show how data-driven theories can explain why chemical compounds behave the way they do, thus promoting a deeper understanding of the essence of chemistry. The text is contributed to by top theoretical and computational chemists who have turned computational chemistry into today’s data-driven and application-oriented science. Exploring Chemical Concepts Through Theory and Computation discusses topics including: Orbital-based approaches, density-based approaches, chemical bonding, partial charges, atoms in molecules, oxidation states, aromaticity and antiaromaticity, and acidity and basicityElectronegativity, hardness, softness, HSAB, sigma-hole interactions, charge transport and energy transfer, and homogeneous and heterogeneous catalysisElectrophilicity, nucleophilicity, cooperativity, frustration, homochirality, and energy decompositionChemical concepts in solids, excited states, spectroscopy and machine learning, and catalysis and machine learning, as well as key connections between related concepts Aimed at both novice and experienced computational, theoretical, and physical chemists, Exploring Chemical Concepts Through Theory and Computation is an essential reference to gain a deeper, more advanced holistic understanding of the field of chemistry as a whole.
Exploring Classical Greek Construction Problems with Interactive Geometry Software
by Ad Meskens Paul TytgatIn this book the classical Greek construction problems are explored in a didactical, enquiry based fashion using Interactive Geometry Software. The book traces the history of these problems, stating them in modern terminology. By focusing on constructions and the use of GeoGebra the reader is confronted with the same problems that ancient mathematicians once faced. The reader can step into the footsteps of Euclid, Vi#65533;te and Cusanus amongst others and then by experimenting and discovering geometric relationships far exceed their accomplishments. Exploring these problems with the neusis-method lets him discover a class of interesting curves. By experimenting he will gain a deeper understanding of how mathematics is created. More than 100 exercises guide him through methods which were developed to try and solve the problems. The exercises are at the level of undergraduate students and only require knowledge of elementary Euclidean geometry and pre-calculus algebra. It is especially well-suited for those students who are thinking of becoming a mathematics teacher and for mathematics teachers.
Exploring Complex Survey Data Analysis Using R: A Tidy Introduction with {srvyr} and {survey}
by Stephanie Zimmer Rebecca Powell Isabella VelásquezSurveys are powerful tools for gathering information, uncovering insights, and facilitating decision-making. However, to ensure the accurate interpretation of results, they require specific analysis methods. In this book, readers embark on an in-depth journey into conducting complex survey analysis with the {srvyr} package and tidyverse family of functions from the R programming language. Intended for intermediate R users familiar with the basics of the tidyverse, this book gives readers a deeper understanding of applying appropriate survey analysis techniques using {srvyr}, {survey}, and other related packages. With practical walkthroughs featuring real-world datasets, such as the American National Election Studies and Residential Energy Consumption Survey, readers will develop the skills necessary to perform impactful survey analysis on survey data collected through a randomized sample design. Additionally, this book teaches readers how to interpret and communicate results of survey data effectively.Key Features: Uses the {srvyr} package and tidyverse family of packages. Grants a conceptual understanding of the statistical methods that the functions apply to. Includes practical walkthroughs using publicly available survey data. Provides the reader with the tools for interpreting, visualizing, and presenting results.
Exploring Data Analysis: The Computer Revolution in Statistics
by W. J. Dixon W. L. Nicholson xxx National Bureau of StandardsThis title is part of UC Press's Voices Revived program, which commemorates University of California Press’s mission to seek out and cultivate the brightest minds and give them voice, reach, and impact. Drawing on a backlist dating to 1893, Voices Revived makes high-quality, peer-reviewed scholarship accessible once again using print-on-demand technology. This title was originally published in 1974.This title is part of UC Press's Voices Revived program, which commemorates University of California Press’s mission to seek out and cultivate the brightest minds and give them voice, reach, and impact. Drawing on a backlist dating to 1893, Voices Revived</DIV