Real Data Analysis
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Real Data Resources For Teachers
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Author :
language : en
Publisher:
Release Date : 1995
Real Data Resources For Teachers written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Mathematics categories.
Guide To Intelligent Data Analysis
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Author : Michael R. Berthold
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-06-23
Guide To Intelligent Data Analysis written by Michael R. Berthold and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-23 with Computers categories.
Each passing year bears witness to the development of ever more powerful computers, increasingly fast and cheap storage media, and even higher bandwidth data connections. This makes it easy to believe that we can now – at least in principle – solve any problem we are faced with so long as we only have enough data. Yet this is not the case. Although large databases allow us to retrieve many different single pieces of information and to compute simple aggregations, general patterns and regularities often go undetected. Furthermore, it is exactly these patterns, regularities and trends that are often most valuable. To avoid the danger of “drowning in information, but starving for knowledge” the branch of research known as data analysis has emerged, and a considerable number of methods and software tools have been developed. However, it is not these tools alone but the intelligent application of human intuition in combination with computational power, of sound background knowledge with computer-aided modeling, and of critical reflection with convenient automatic model construction, that results in successful intelligent data analysis projects. Guide to Intelligent Data Analysis provides a hands-on instructional approach to many basic data analysis techniques, and explains how these are used to solve data analysis problems. Topics and features: guides the reader through the process of data analysis, following the interdependent steps of project understanding, data understanding, data preparation, modeling, and deployment and monitoring; equips the reader with the necessary information in order to obtain hands-on experience of the topics under discussion; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; includes numerous examples using R and KNIME, together with appendices introducing the open source software; integrates illustrations and case-study-style examplesto support pedagogical exposition. This practical and systematic textbook/reference for graduate and advanced undergraduate students is also essential reading for all professionals who face data analysis problems. Moreover, it is a book to be used following one’s exploration of it. Dr. Michael R. Berthold is Nycomed-Professor of Bioinformatics and Information Mining at the University of Konstanz, Germany. Dr. Christian Borgelt is Principal Researcher at the Intelligent Data Analysis and Graphical Models Research Unit of the European Centre for Soft Computing, Spain. Dr. Frank Höppner is Professor of Information Systems at Ostfalia University of Applied Sciences, Germany. Dr. Frank Klawonn is a Professor in the Department of Computer Science and Head of the Data Analysis and Pattern Recognition Laboratory at Ostfalia University of Applied Sciences, Germany. He is also Head of the Bioinformatics and Statistics group at the Helmholtz Centre for Infection Research, Braunschweig, Germany.
Computational Intelligence Volume I
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Author : Hisao Ishibuchi
language : en
Publisher: EOLSS Publications
Release Date : 2015-12-30
Computational Intelligence Volume I written by Hisao Ishibuchi and has been published by EOLSS Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-30 with categories.
Computational intelligence is a component of Encyclopedia of Technology, Information, and Systems Management Resources in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. Computational intelligence is a rapidly growing research field including a wide variety of problem-solving techniques inspired by nature. Traditionally computational intelligence consists of three major research areas: Neural Networks, Fuzzy Systems, and Evolutionary Computation. Neural networks are mathematical models inspired by brains. Neural networks have massively parallel network structures with many neurons and weighted connections. Whereas each neuron has a simple input-output relation, a neural network with many neurons can realize a highly non-linear complicated mapping. Connection weights between neurons can be adjusted in an automated manner by a learning algorithm to realize a non-linear mapping required in a particular application task. Fuzzy systems are mathematical models proposed to handle inherent fuzziness in natural language. For example, it is very difficult to mathematically define the meaning of “cold” in everyday conversations such as “It is cold today” and “Can I have cold water”. The meaning of “cold” may be different in a different situation. Even in the same situation, a different person may have a different meaning. Fuzzy systems offer a mathematical mechanism to handle inherent fuzziness in natural language. As a result, fuzzy systems have been successfully applied to real-world problems by extracting linguistic knowledge from human experts in the form of fuzzy IF-THEN rules. Evolutionary computation includes various population-based search algorithms inspired by evolution in nature. Those algorithms usually have the following three mechanisms: fitness evaluation to measure the quality of each solution, selection to choose good solutions from the current population, and variation operators to generate offspring from parents. Evolutionary computation has high applicability to a wide range of optimization problems with different characteristics since it does not need any explicit mathematical formulations of objective functions. For example, simulation-based fitness evaluation is often used in evolutionary design. Subjective fitness evaluation by a human user is also often used in evolutionary art and music. These volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers.
Real Data Analysis
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Author : Shlomo S. Sawilowsky
language : en
Publisher: Emerald Group Publishing
Release Date : 2006-12-15
Real Data Analysis written by Shlomo S. Sawilowsky and has been published by Emerald Group Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-12-15 with Education categories.
This edited volume showcases the prolific work of authors in Real Data Analysis (RDA) in social and behavioral sciences, especially education and psychology. It highlights their extensive publications, research funding, awards, and editorial roles, making it a valuable resource for academics and students.
Statistical Portfolio Estimation
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Author : Masanobu Taniguchi
language : en
Publisher: CRC Press
Release Date : 2017-09-01
Statistical Portfolio Estimation written by Masanobu Taniguchi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-01 with Mathematics categories.
The composition of portfolios is one of the most fundamental and important methods in financial engineering, used to control the risk of investments. This book provides a comprehensive overview of statistical inference for portfolios and their various applications. A variety of asset processes are introduced, including non-Gaussian stationary processes, nonlinear processes, non-stationary processes, and the book provides a framework for statistical inference using local asymptotic normality (LAN). The approach is generalized for portfolio estimation, so that many important problems can be covered. This book can primarily be used as a reference by researchers from statistics, mathematics, finance, econometrics, and genomics. It can also be used as a textbook by senior undergraduate and graduate students in these fields.
Sharing Social Science Data
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Author : Joan E. Sieber
language : en
Publisher: SAGE
Release Date : 1991-02-12
Sharing Social Science Data written by Joan E. Sieber and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991-02-12 with Computers categories.
This book represents the major accomplishments of social scientists who have pioneered in data sharing, highlighting the advantages for social science. It includes an examination of the reasons for data sharing, the specific sharing practices in various disciplines, the factors affecting the usefulness of shared data and individual and institutional concerns about data sharing. It will be useful to academics across the social sciences.
Knowledge Based Intelligent Information And Engineering Systems
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Author : Bogdan Gabrys
language : en
Publisher: Springer
Release Date : 2006-10-11
Knowledge Based Intelligent Information And Engineering Systems written by Bogdan Gabrys and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-10-11 with Computers categories.
The three volume set LNAI 4251, LNAI 4252, and LNAI 4253 constitutes the refereed proceedings of the 10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006, held in Bournemouth, UK, in October 2006. The 480 revised papers presented were carefully reviewed and selected from about 1400 submissions. The papers present a wealth of original research results from the field of intelligent information processing.
Data Analytics For Absolute Beginners A Deconstructed Guide To Data Literacy
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Author : Oliver Theobald
language : en
Publisher:
Release Date : 2019-07-21
Data Analytics For Absolute Beginners A Deconstructed Guide To Data Literacy written by Oliver Theobald and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-21 with categories.
While exposure to data has become more or less a daily ritual for the rank-and-file knowledge worker, true understanding-treated in this book as data literacy-resides in knowing what lies behind the data. Everything from the data's source to the specific choice of input variables, algorithmic transformations, and visual representation shape the accuracy, relevance, and value of the data and mark its journey from raw data to business insight. It's also important to grasp the terminology and basic concepts of data analytics as much as it is to have the financial literacy to be successful as a decisionmaker in the business world. In this book, we make sense of data analytics without the assumption that you understand specific data science terminology or advanced programming languages to set you on your path. Topics covered in this book: Data Mining Big Data Machine Learning Alternative Data Data Management Web Scraping Regression Analysis Clustering Analysis Association Analysis Data Visualization Business Intelligence
Longitudinal Multivariate Psychology
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Author : Emilio Ferrer
language : en
Publisher: Routledge
Release Date : 2018-10-09
Longitudinal Multivariate Psychology written by Emilio Ferrer and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-09 with Psychology categories.
This volume presents a collection of chapters focused on the study of multivariate change. As people develop and change, multivariate measurement of that change and analysis of those measures can illuminate the regularities in the trajectories of individual development, as well as time-dependent changes in population averages. As longitudinal data have recently become much more prevalent in psychology and the social sciences, models of change have become increasingly important. This collection focuses on methodological, statistical, and modeling aspects of multivariate change and applications of longitudinal models to the study of psychological processes. The volume is divided into three major sections: Extension of latent change models, Measurement and testing issues in longitudinal modeling, and Novel applications of multivariate longitudinal methodology. It is intended for advanced students and researchers interested in learning about state-of-the-art techniques for longitudinal data analysis, as well as understanding the history and development of such techniques.
A Critical Evaluation Of The Criticisms Against Neutrosophic Statistical Methods
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Author : Muhammad Aslam
language : en
Publisher: Infinite Study
Release Date :
A Critical Evaluation Of The Criticisms Against Neutrosophic Statistical Methods written by Muhammad Aslam and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.
Neutrosophic statistical analysis has gained attention for incorporating the degree of indeterminacy when analyzing imprecise and interval data under uncertainty—an aspect often overlooked by classical statistics, fuzzy statistical analysis, and interval statistics. Recently, critical discussions have emerged regarding the use and applications of neutrosophic statistics, with some questioning its usefulness and validity. In this paper, we present a critical assessment of the existing literature, focusing on areas where misunderstandings and misinterpretations of neutrosophic statistical methods have occurred. We also examine flawed comparisons made between the results of neutrosophic statistics and interval statistics. Furthermore, substantial issues have been identified in the current simulation, both in its application and in the comparison of results. The objective of this paper is to highlight these key concerns and provide clarity for researchers working in this area, helping them to better understand the appropriate applications of neutrosophic statistical methods.