Applied Modeling Techniques and Data Analysis 1: Computational Data Analysis Methods and Tools, Karagrigoriou Alex, Parpoula Christina, Dimotikalis Yannis
Автор: Little Название: Statistical Analysis with Missing Data, Third Edit ion ISBN: 0470526793 ISBN-13(EAN): 9780470526798 Издательство: Wiley Рейтинг: Цена: 12664.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Reflecting new application topics, Statistical Analysis with Missing Data offers a thoroughly up-to-date, reorganized survey of current methodology for handling missing data problems. The third edition reviews historical approaches to the subject and describe rigorous yet simple methods for multivariate analysis with missing values.
Описание: Can we coexist with the other life forms that have evolved on this planet? Are there realistic alternatives to fossil fuels that would sustainably provide for human society's energy needs and have fewer harmful effects? How do we deal with threats such as emergent diseases? Mathematical models--equations of various sorts capturing relationships between variables involved in a complex situation--are fundamental for understanding the potential consequences of choices we make. Extracting insights from the vast amounts of data we are able to collect requires analysis methods and statistical reasoning.This book on elementary topics in mathematical modeling and data analysis is intended for an undergraduate ``liberal arts mathematics''-type course but with a specific focus on environmental applications. It is suitable for introductory courses with no prerequisites beyond high school mathematics. A great variety of exercises extends the discussions of the main text to new situations and/or introduces new real-world examples. Every chapter ends with a section of problems, as well as with an extended chapter project which often involves substantial computing work either in spreadsheet software or in the ${\tt R}$ statistical package.
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.
It contains
Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
Includes open-access online courses that introduce practical applications of the material in the book
Автор: Kristi Jackson, Patricia Bazeley Название: Qualitative Data Analysis with NVivo ISBN: 1526449935 ISBN-13(EAN): 9781526449931 Издательство: Sage Publications Рейтинг: Цена: 17424.00 р. Наличие на складе: Поставка под заказ.
Описание: Practical, focused and jargon-free this book shows you the power and potential of NVivo software across a wide range of research questions, data types, perspectives and methodologies.
Описание: ?? Provides a concise but rigorous account of the theoretical background of FDA. ?? Introduces topics in various areas of mathematics, probability and statistics from the perspective of FDA. ?? Presents a systematic exposition of the fundamental statistical issues in FDA.
Описание: This is a textbook on classical polynomial and rational approximation theory for the twenty-first century. Aimed at advanced undergraduates and graduate students across all of applied mathematics, it uses MATLAB to teach the field’s most important ideas and results.
Approximation Theory and Approximation Practice, Extended Edition differs fundamentally from other works on approximation theory in a number of ways: its emphasis is on topics close to numerical algorithms; concepts are illustrated with Chebfun; and each chapter is a PUBLISHable MATLAB M-file, available online.
The book centers on theorems and methods for analytic functions, which appear so often in applications, rather than on functions at the edge of discontinuity with their seductive theoretical challenges. Original sources are cited rather than textbooks, and each item in the bibliography is accompanied by an editorial comment. In addition, each chapter has a collection of exercises, which span a wide range from mathematical theory to Chebfun-based numerical experimentation.
Автор: Heath Rose; Jim McKinley Название: Data Collection Research Methods in Applied Linguistics ISBN: 1350025844 ISBN-13(EAN): 9781350025844 Издательство: Bloomsbury Academic Рейтинг: Цена: 5067.00 р. Наличие на складе: Нет в наличии.
Описание:
The successful collection of data is a key challenge to obtaining reliable and valid results in applied linguistics research. Data Collection Research Methods in Applied Linguistics investigates how research is conducted in the field, encompassing the challenges and obstacles applied linguists face in collecting good data. The book explores frequently used data collection techniques, including:
* interviews and focus groups * observations * stimulated recall and think aloud protocols * data elicitation tasks * corpus methods * questionnaires * validated tests and measures
Each chapter focuses on one type of data collection, outlining key concepts, threats to reliability and validity, procedures for good data collection, and implications for researchers. The chapters also include exemplary research projects, showcasing and explaining for readers how the technique was used to collect data in a successfully published study. This book is an essential resource for both novice and experienced applied linguists tackling data collection techniques for the first time.
BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen
Data analysis is a scientific field that continues to grow enormously, most notably over the last few decades, following rapid growth within the tech industry, as well as the wide applicability of computational techniques alongside new advances in analytic tools. Modeling enables data analysts to identify relationships, make predictions, and to understand, interpret and visualize the extracted information more strategically.
This book includes the most recent advances on this topic, meeting increasing demand from wide circles of the scientific community. Applied Modeling Techniques and Data Analysis 2 is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians, working on the front end of data analysis and modeling applications. The chapters cover a cross section of current concerns and research interests in the above scientific areas. The collected material is divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications.
Описание: This book will help readers acquire knowledge and equip them in handling various statistical and financial computations using MS Excel.
The book is designed to equip students to navigate through MS Excel spreadsheets to compute various statistical and financial measures for use in data analysis.
Basic Computational Techniques for Data Analysis illustrates the concepts used in economic and financial decision-making in business as well as in day-to-day life, thus enhancing a deeper understanding of the concepts from both theoretical and practical perspectives. After going through the textbook, readers will be able to ascertain the inbuilt capabilities in MS Excel and comprehend basic computations in statistics and finance.
This book is essential as a supportive companion for students of economics, commerce, management and social science subjects in general.
Key Features:
•Provides an in-depth and clear understanding of various data analysis techniques
•Systemic and stepwise explanation of financial and statistical concepts using MS Excel functions
•Prior knowledge of statistics, finance and MS-Excel functions not required to understand the concepts
•Simplistic clarification of topics such as Future Value of Money, Loan Amortization and Investment Decision Criteria
Описание: Two-sided matching provides a model of search processes such as those between firms and workers in labor markets or between buyers and sellers in auctions. This text provides a comprehensive account of recent results concerning the game-theoretic analysis of two-sided matching.
Автор: Petr N. Vabishchevich Название: Computational Technologies: Advanced Topics ISBN: 3110359944 ISBN-13(EAN): 9783110359947 Издательство: Walter de Gruyter Цена: 9288.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book discusses questions of numerical solutions of applied problems on parallel computing systems. Nowadays, engineering and scientific computations are carried out on parallel computing systems, which provide parallel data processing on a few computing nodes. In the development of up-to-date applied software, this feature of computers must be taken into account for the maximum efficient usage of their resources. In constructing computational algorithms, we should separate relatively independent subproblems in order to solve them on a single computing node.
Описание: Metabolomics and proteomics allow deep insights into the chemistry and physiological processes of biological systems. This book will enable researchers, practitioners and students from different backgrounds to analyze metabolomics and proteomics mass spectrometry data.
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