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Applied Statistics I: Basic Bivariate Techniques

by Rebecca M. Warner

Rebecca M. Warner&’s bestselling Applied Statistics: From Bivariate Through Multivariate Techniques has been split into two volumes for ease of use over a two-course sequence. Applied Statistics I: Basic Bivariate Techniques, Third Edition is an introductory statistics text based on chapters from the first half of the original book. The author's contemporary approach reflects current thinking in the field, with its coverage of the "new statistics" and reproducibility in research. Her in-depth presentation of introductory statistics follows a consistent chapter format, includes some simple hand-calculations along with detailed instructions for SPSS, and helps students understand statistics in the context of real-world research through interesting examples. Datasets are provided on an accompanying website.

Applied Statistics I: Basic Bivariate Techniques

by Rebecca M. Warner

Rebecca M. Warner&’s bestselling Applied Statistics: From Bivariate Through Multivariate Techniques has been split into two volumes for ease of use over a two-course sequence. Applied Statistics I: Basic Bivariate Techniques, Third Edition is an introductory statistics text based on chapters from the first half of the original book. The author's contemporary approach reflects current thinking in the field, with its coverage of the "new statistics" and reproducibility in research. Her in-depth presentation of introductory statistics follows a consistent chapter format, includes some simple hand-calculations along with detailed instructions for SPSS, and helps students understand statistics in the context of real-world research through interesting examples. Datasets are provided on an accompanying website.

Applied Statistics II: Multivariable and Multivariate Techniques

by Rebecca M. Warner

Rebecca M. Warner&’s bestselling Applied Statistics: From Bivariate Through Multivariate Techniques has been split into two volumes for ease of use over a two-course sequence. Applied Statistics II: Multivariable and Multivariate Techniques, Third Edition is a core multivariate statistics text based on chapters from the second half of the original book. The text begins with two new chapters: an introduction to the new statistics, and a chapter on handling outliers and missing values. All chapters on statistical control and multivariable or multivariate analyses from the previous edition are retained (with the moderation chapter heavily revised) and new chapters have been added on structural equation modeling, repeated measures, and on additional statistical techniques. Each chapter includes a complete example, and begins by considering the types of research questions that chapter&’s technique can answer, progresses to data screening, and provides screen shots of SPSS menu selections and output, and concludes with sample results sections. By-hand computation is used, where possible, to show how elements of the output are related to each other, and to obtain confidence interval and effect size information when SPSS does not provide this. Datasets are available on the accompanying website.

Applied Statistics II: Multivariable and Multivariate Techniques

by Rebecca M. Warner

Rebecca M. Warner&’s bestselling Applied Statistics: From Bivariate Through Multivariate Techniques has been split into two volumes for ease of use over a two-course sequence. Applied Statistics II: Multivariable and Multivariate Techniques, Third Edition is a core multivariate statistics text based on chapters from the second half of the original book. The text begins with two new chapters: an introduction to the new statistics, and a chapter on handling outliers and missing values. All chapters on statistical control and multivariable or multivariate analyses from the previous edition are retained (with the moderation chapter heavily revised) and new chapters have been added on structural equation modeling, repeated measures, and on additional statistical techniques. Each chapter includes a complete example, and begins by considering the types of research questions that chapter&’s technique can answer, progresses to data screening, and provides screen shots of SPSS menu selections and output, and concludes with sample results sections. By-hand computation is used, where possible, to show how elements of the output are related to each other, and to obtain confidence interval and effect size information when SPSS does not provide this. Datasets are available on the accompanying website.

Bringing Bayesian Models to Life (Chapman & Hall/CRC Applied Environmental Statistics)

by Mevin B. Hooten Trevor J. Hefley

Bringing Bayesian Models to Life empowers the reader to extend, enhance, and implement statistical models for ecological and environmental data analysis. We open the black box and show the reader how to connect modern statistical models to computer algorithms. These algorithms allow the user to fit models that answer their scientific questions without needing to rely on automated Bayesian software. We show how to handcraft statistical models that are useful in ecological and environmental science including: linear and generalized linear models, spatial and time series models, occupancy and capture-recapture models, animal movement models, spatio-temporal models, and integrated population-models. Features: R code implementing algorithms to fit Bayesian models using real and simulated data examples. A comprehensive review of statistical models commonly used in ecological and environmental science. Overview of Bayesian computational methods such as importance sampling, MCMC, and HMC. Derivations of the necessary components to construct statistical algorithms from scratch. Bringing Bayesian Models to Life contains a comprehensive treatment of models and associated algorithms for fitting the models to data. We provide detailed and annotated R code in each chapter and apply it to fit each model we present to either real or simulated data for instructional purposes. Our code shows how to create every result and figure in the book so that readers can use and modify it for their own analyses. We provide all code and data in an organized set of directories available at the authors' websites.

Discrete Mathematical Structures: A Succinct Foundation (Mathematics and its Applications)

by Hemen Dutta B. V. Kumar

This book contains fundamental concepts on discrete mathematical structures in an easy to understand style so that the reader can grasp the contents and explanation easily. The concepts of discrete mathematical structures have application to computer science, engineering and information technology including in coding techniques, switching circuits, pointers and linked allocation, error corrections, as well as in data networking, Chemistry, Biology and many other scientific areas. The book is for undergraduate and graduate levels learners and educators associated with various courses and progammes in Mathematics, Computer Science, Engineering and Information Technology. The book should serve as a text and reference guide to many undergraduate and graduate programmes offered by many institutions including colleges and universities. Readers will find solved examples and end of chapter exercises to enhance reader comprehension. Features Offers comprehensive coverage of basic ideas of Logic, Mathematical Induction, Graph Theory, Algebraic Structures and Lattices and Boolean Algebra Provides end of chapter solved examples and practice problems Delivers materials on valid arguments and rules of inference with illustrations Focuses on algebraic structures to enable the reader to work with discrete structures

A Guide to R for Social and Behavioral Science Statistics

by Brian Joseph Gillespie Dr. William E. Wagner Kathleen Charli Hibbert

A Guide to R for Social and Behavioral Science Statistics is a short, accessible book for learning R, geared toward social and behavioral science students. Instructors Brian Gillespie, Kathleen Hibbert, and William E. Wagner, III, have combined a review of introductory statistics with an introduction to R to teach readers two of the most valuable skills for research and in the workplace. Designed for readers with no knowledge of statistics or R, A Guide to R for Social and Behavioral Science Statistics follows the most common progression of statistics, starting with basic descriptive statistics, and continuing up through inferential statistics and regression. This text provides step-by-step instructions for working with R, starting with downloading and installing R and RStudio®, featuring code and output so readers can follow along with each step. Readers can apply their knowledge with examples and exercises featuring data from the General Social Survey in each chapter. Tips on R show users how to avoid common pitfalls in R and most efficiently use the RStudio interface. With frequent reminders of statistical concepts to accompany instructions and tips in R, this text helps readers master R for statistics in the social and behavioral sciences.

A Guide to R for Social and Behavioral Science Statistics

by Brian Joseph Gillespie Dr. William E. Wagner Kathleen Charli Hibbert

A Guide to R for Social and Behavioral Science Statistics is a short, accessible book for learning R, geared toward social and behavioral science students. Instructors Brian Gillespie, Kathleen Hibbert, and William E. Wagner, III, have combined a review of introductory statistics with an introduction to R to teach readers two of the most valuable skills for research and in the workplace. Designed for readers with no knowledge of statistics or R, A Guide to R for Social and Behavioral Science Statistics follows the most common progression of statistics, starting with basic descriptive statistics, and continuing up through inferential statistics and regression. This text provides step-by-step instructions for working with R, starting with downloading and installing R and RStudio®, featuring code and output so readers can follow along with each step. Readers can apply their knowledge with examples and exercises featuring data from the General Social Survey in each chapter. Tips on R show users how to avoid common pitfalls in R and most efficiently use the RStudio interface. With frequent reminders of statistical concepts to accompany instructions and tips in R, this text helps readers master R for statistics in the social and behavioral sciences.

Mathematical Methods in Engineering and Applied Sciences (Mathematics and its Applications)

by Hemen Dutta

This book covers tools and techniques used for developing mathematical methods and modelling related to real-life situations. It brings forward significant aspects of mathematical research by using different mathematical methods such as analytical, computational, and numerical with relevance or applications in engineering and applied sciences. Presents theory, methods, and applications in a balanced manner Includes the basic developments with full details Contains the most recent advances and offers enough references for further study Written in a self-contained style and provides proof of necessary results Offers research problems to help early career researchers prepare research proposals Mathematical Methods in Engineering and Applied Sciences makes available for the audience, several relevant topics in one place necessary for crucial understanding of research problems of an applied nature. This should attract the attention of general readers, mathematicians, and engineers interested in new tools and techniques required for developing more accurate mathematical methods and modelling corresponding to real-life situations.

Optimization Using Evolutionary Algorithms and Metaheuristics: Applications in Engineering (Science, Technology, and Management)

by J. Paulo Davim Kaushik Kumar

Metaheuristic optimization is a higher-level procedure or heuristic designed to find, generate, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem, especially with incomplete or imperfect information or limited computation capacity. This is usually applied when two or more objectives are to be optimized simultaneously. This book is presented with two major objectives. Firstly, it features chapters by eminent researchers in the field providing the readers about the current status of the subject. Secondly, algorithm-based optimization or advanced optimization techniques, which are applied to mostly non-engineering problems, are applied to engineering problems. This book will also serve as an aid to both research and industry. Usage of these methodologies would enable the improvement in engineering and manufacturing technology and support an organization in this era of low product life cycle. Features: Covers the application of recent and new algorithms Focuses on the development aspects such as including surrogate modeling, parallelization, game theory, and hybridization Presents the advances of engineering applications for both single-objective and multi-objective optimization problems Offers recent developments from a variety of engineering fields Discusses Optimization using Evolutionary Algorithms and Metaheuristics applications in engineering

An R Companion for Applied Statistics I: Basic Bivariate Techniques

by Danney Rasco

An R Companion for Applied Statistics I: Basic Bivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use it. R is a powerful, flexible, and free tool. However, the flexibility—which eventually becomes a great asset—can make the initial learning curve appear steep. This book introduces a few key aspects of the R tool. As readers become comfortable with these aspects, they develop a foundation from which to more thoroughly explore R and the packages available for it. This introduction does not explain every possible way to analyze data or perform a specific type of analysis. Rather, it focuses on the analyses that are traditionally included in an undergraduate statistics course and provides one or two ways to run these analyses in R. Datasets and scripts to run the examples are provided on an accompanying website. The book has been designed to be an R companion to Warner's Applied Statistics I, Third Edition, and includes end-of-chapter instructions for replicating the examples from that book in R. However, this text can also be used as a stand-alone R guide, without reference to the Warner text.

An R Companion for Applied Statistics I: Basic Bivariate Techniques

by Danney Rasco

An R Companion for Applied Statistics I: Basic Bivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use it. R is a powerful, flexible, and free tool. However, the flexibility—which eventually becomes a great asset—can make the initial learning curve appear steep. This book introduces a few key aspects of the R tool. As readers become comfortable with these aspects, they develop a foundation from which to more thoroughly explore R and the packages available for it. This introduction does not explain every possible way to analyze data or perform a specific type of analysis. Rather, it focuses on the analyses that are traditionally included in an undergraduate statistics course and provides one or two ways to run these analyses in R. Datasets and scripts to run the examples are provided on an accompanying website. The book has been designed to be an R companion to Warner's Applied Statistics I, Third Edition, and includes end-of-chapter instructions for replicating the examples from that book in R. However, this text can also be used as a stand-alone R guide, without reference to the Warner text.

Recent Advances in Mathematics for Engineering (Mathematical Engineering, Manufacturing, and Management Sciences)

by Mangey Ram

In recent years, mathematics has experienced amazing growth in the engineering sciences. Mathematics forms the common foundation of all engineering disciplines. This book provides a comprehensive range of mathematics applied in various fields of engineering for different tasks such as civil engineering, structural engineering, computer science, and electrical engineering, among others. It offers chapters that develop the applications of mathematics in engineering sciences, conveys the innovative research ideas, offers real-world utility of mathematics, and has a significance in the life of academics, practitioners, researchers, and industry leaders. Features Focuses on the latest research in the field of engineering applications Includes recent findings from various institutions Identifies the gaps in the knowledge in the field and provides the latest approaches Presents international studies and findings in modeling and simulation Offers various mathematical tools, techniques, strategies, and methods across different engineering fields

Social Statistics for a Diverse Society

by Georgiann Davis Dr. Chava Frankfort-Nachmias Dr. Anna Y. Leon-Guerrero

The Ninth Edition of Social Statistics for a Diverse Society continues to emphasize intuition and common sense, while demonstrating the link between the practice of statistics and important social issues. Recognizing that we live in a world characterized by a growing diversity and richness of social differences, best-selling authors Frankfort-Nachmias, Leon-Guerrero, and Davis help you learn key statistical concepts through real research examples related to the dynamic interplay of race, class, gender, and other social variables. The text also helps you develop important skills such as problem-solving (through a rich variety of exercises), use of statistical software (both SPSS and Excel), and interpreting research literature.

Social Statistics for a Diverse Society

by Georgiann Davis Dr. Chava Frankfort-Nachmias Dr. Anna Y. Leon-Guerrero

The Ninth Edition of Social Statistics for a Diverse Society continues to emphasize intuition and common sense, while demonstrating the link between the practice of statistics and important social issues. Recognizing that we live in a world characterized by a growing diversity and richness of social differences, best-selling authors Frankfort-Nachmias, Leon-Guerrero, and Davis help you learn key statistical concepts through real research examples related to the dynamic interplay of race, class, gender, and other social variables. The text also helps you develop important skills such as problem-solving (through a rich variety of exercises), use of statistical software (both SPSS and Excel), and interpreting research literature.

Statistics: A Gentle Introduction

by Dr. Frederick L. Coolidge

The Fourth Edition of Statistics: A Gentle Introduction shows students that an introductory statistics class doesn&’t need to be difficult or dull. Author Fred Coolidge minimizes students&’ anxieties about math by explaining the concepts of statistics in plain language first, before addressing the math. Each formula within the text has a step-by-step example to demonstrate the calculation so students can follow along. Only those formulas that are important for final calculations are included in the text so students can focus on the concepts, not the numbers. A wealth of real-world examples and applications gives a context for statistics in the real world and how it helps us solve problems and make informed choices. New to the Fourth Edition are sections on working with big data, new coverage of alternative non-parametric tests, beta coefficients, and the "nocebo effect," discussions of p values in the context of research, an expanded discussion of confidence intervals, and more exercises and homework options under the new feature "Test Yourself."

Statistics: A Gentle Introduction

by Dr. Frederick L. Coolidge

The Fourth Edition of Statistics: A Gentle Introduction shows students that an introductory statistics class doesn&’t need to be difficult or dull. Author Fred Coolidge minimizes students&’ anxieties about math by explaining the concepts of statistics in plain language first, before addressing the math. Each formula within the text has a step-by-step example to demonstrate the calculation so students can follow along. Only those formulas that are important for final calculations are included in the text so students can focus on the concepts, not the numbers. A wealth of real-world examples and applications gives a context for statistics in the real world and how it helps us solve problems and make informed choices. New to the Fourth Edition are sections on working with big data, new coverage of alternative non-parametric tests, beta coefficients, and the "nocebo effect," discussions of p values in the context of research, an expanded discussion of confidence intervals, and more exercises and homework options under the new feature "Test Yourself."

Statistics With R: Solving Problems Using Real-World Data

by Jenine K. Harris

Drawing on examples from across the social and behavioral sciences, Statistics with R: Solving Problems Using Real-World Data by Jenine K. Harris introduces foundational statistics concepts with beginner-friendly R programming in an exploration of the world&’s tricky problems faced by the &“R Team&” characters. Inspired by the programming group &“R Ladies,&” the R Team works together to master the skills of statistical analysis and data visualization to untangle real-world, messy data using R. The storylines draw students into investigating contemporary issues such as marijuana legalization, voter registration, and the opioid epidemic, and lead them step-by-step through full-color illustrations of R statistics and interactive exercises.

Statistics With R: Solving Problems Using Real-World Data

by Jenine K. Harris

Drawing on examples from across the social and behavioral sciences, Statistics with R: Solving Problems Using Real-World Data by Jenine K. Harris introduces foundational statistics concepts with beginner-friendly R programming in an exploration of the world&’s tricky problems faced by the &“R Team&” characters. Inspired by the programming group &“R Ladies,&” the R Team works together to master the skills of statistical analysis and data visualization to untangle real-world, messy data using R. The storylines draw students into investigating contemporary issues such as marijuana legalization, voter registration, and the opioid epidemic, and lead them step-by-step through full-color illustrations of R statistics and interactive exercises.

12th Chaotic Modeling and Simulation International Conference (Springer Proceedings in Complexity)

by Christos H. Skiadas Yiannis Dimotikalis

Gathering the proceedings of the 12th CHAOS2019 International Conference, this book highlights recent developments in nonlinear, dynamical and complex systems. The conference was intended to provide an essential forum for Scientists and Engineers to exchange ideas, methods, and techniques in the field of Nonlinear Dynamics, Chaos, Fractals and their applications in General Science and the Engineering Sciences. The respective chapters address key methods, empirical data and computer techniques, as well as major theoretical advances in the applied nonlinear field. Beyond showcasing the state of the art, the book will help academic and industrial researchers alike apply chaotic theory in their studies.

2⁵ Problems for STEM Education

by Valery Ochkov

25 Problems for STEM Education introduces a new and emerging course for undergraduate STEM programs called Physical-Mathematical Informatics. This course corresponds with the new direction in education called STE(A)M (Science, Technology, Engineering, [Art] and Mathematics). The book focuses on undergraduate university students (and high school students), as well as the teachers of mathematics, physics, chemistry and other disciplines such as the humanities. This book is suitable for readers who have a basic understanding of mathematics and math software. Features Contains 32 interesting problems (studies) and new and unique methods of solving these physical and mathematical problems using a computer as well as new methods of teaching mathematics and physics Suitable for students in advanced high school courses and undergraduates, as well as for students studying Mathematical Education at the Master’s or PhD level One of the only books that attempts to bring together ST(E)AM techniques, computational mathematics and informatics in a single, unified format

The 21st Century Singularity and Global Futures: A Big History Perspective (World-Systems Evolution and Global Futures)

by Andrey V. Korotayev David J. LePoire

This book introduces a 'Big History' perspective to understand the acceleration of social, technological and economic trends towards a near-term singularity, marking a radical turning point in the evolution of our planet. It traces the emergence of accelerating innovation rates through global history and highlights major historical transformations throughout the evolution of life, humans, and civilization. The authors pursue an interdisciplinary approach, also drawing on concepts from physics and evolutionary biology, to offer potential models of the underlying mechanisms driving this acceleration, along with potential clues on how it might progress. The contributions gathered here are divided into five parts, the first of which studies historical mega-trends in relation to a variety of aspects including technology, population, energy, and information. The second part is dedicated to a variety of models that can help understand the potential mechanisms, and support extrapolation. In turn, the third part explores various potential future scenarios, along with the paths and decisions that are required. The fourth part presents philosophical perspectives on the potential deeper meaning and implications of the trend towards singularity, while the fifth and last part discusses the implications of the Search for Extraterrestrial Intelligence (SETI). Given its scope, the book will appeal to scholars from various disciplines interested in historical trends, technological change and evolutionary processes.

50 Years of CFD in Engineering Sciences: A Commemorative Volume in Memory of D. Brian Spalding

by Akshai Runchal

Prof. D. Brian Spalding, working with a small group of students and colleagues at Imperial College, London in the mid-to late-1960’s, single-handedly pioneered the use of Computational Fluid Dynamics (CFD) for engineering practice.​This book brings together advances in computational fluid dynamics in a collection of chapters authored by leading researchers, many of them students or associates of Prof. Spalding. The book intends to capture the key developments in specific fields of activity that have been transformed by application of CFD in the last 50 years. The focus is on review of the impact of CFD on these selected fields and of the novel applications that CFD has made possible. Some of the chapters trace the history of developments in a specific field and the role played by Spalding and his contributions. The volume also includes a biographical summary of Brian Spalding as a person and as a scientist, as well as tributes to Brian Spalding by those whose life was impacted by his innovations. This volume would be of special interest to researchers, practicing engineers, and graduate students in various fields, including aerospace, energy, power and propulsion, transportation, combustion, management of the environment, health and pharmaceutical sciences.

50 years of Combinatorics, Graph Theory, and Computing (Discrete Mathematics and Its Applications)

by Ron Graham Leslie Hogben Fan Chung Frederick Hoffman Ronald C. Mullin Douglas B. West

50 Years of Combinatorics, Graph Theory, and Computing advances research in discrete mathematics by providing current research surveys, each written by experts in their subjects. The book also celebrates outstanding mathematics from 50 years at the Southeastern International Conference on Combinatorics, Graph Theory & Computing (SEICCGTC). The conference is noted for the dissemination and stimulation of research, while fostering collaborations among mathematical scientists at all stages of their careers. The authors of the chapters highlight open questions. The sections of the book include: Combinatorics; Graph Theory; Combinatorial Matrix Theory; Designs, Geometry, Packing and Covering. Readers will discover the breadth and depth of the presentations at the SEICCGTC, as well as current research in combinatorics, graph theory and computer science. Features: Commemorates 50 years of the Southeastern International Conference on Combinatorics, Graph Theory & Computing with research surveys Surveys highlight open questions to inspire further research Chapters are written by experts in their fields Extensive bibliographies are provided at the end of each chapter

Ab initio Theory of Magnetic Ordering: Electronic Origin of Pair- and Multi-Spin Interactions (Springer Theses)

by Eduardo Mendive Tapia

Many technological applications exploit a variety of magnetic structures, or magnetic phases, to produce and optimise solid-state functionality. However, most research advances are restricted to a reduced number of phases owing to computational and resource constraints. This thesis presents an ab-initio theory to efficiently describe complex magnetic phases and their temperature-dependent properties. The central assumption is that magnetic phases evolve slowly compared with the underlying electronic structure from which they emerge. By describing how the electronic structure adapts to the type and extent of magnetic order, a theory able to describe multi-spin correlations and their effect on the magnetism at finite temperature is obtained. It is shown that multi-spin correlations are behind the temperature and magnetic field dependence of the diverse magnetism in the heavy rare earth elements. Magnetically frustrated Mn-based materials and the effect of strain are also investigated. These studies demonstrate that the performance of solid-state refrigeration can be enhanced by multi-spin effects.

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