Advances In Statistical Methodologies And Their Application To Real Problems
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Advances In Statistical Methodologies And Their Application To Real Problems
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Author : Tsukasa Hokimoto
language : en
Publisher: BoD – Books on Demand
Release Date : 2017-04-26
Advances In Statistical Methodologies And Their Application To Real Problems written by Tsukasa Hokimoto and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-26 with Mathematics categories.
In recent years, statistical techniques and methods for data analysis have advanced significantly in a wide range of research areas. These developments enable researchers to analyze increasingly large datasets with more flexibility and also more accurately estimate and evaluate the phenomena they study. We recognize the value of recent advances in data analysis techniques in many different research fields. However, we also note that awareness of these different statistical and probabilistic approaches may vary, owing to differences in the datasets typical of different research fields. This book provides a cross-disciplinary forum for exploring the variety of new data analysis techniques emerging from different fields.
Advances In Statistical Methodologies And Their Application To Real Problems
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Author :
language : en
Publisher:
Release Date : 19??
Advances In Statistical Methodologies And Their Application To Real Problems written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 19?? with categories.
Probability Theory And Statistical Inference
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Author : Aris Spanos
language : en
Publisher: Cambridge University Press
Release Date : 2019-09-19
Probability Theory And Statistical Inference written by Aris Spanos and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-19 with Business & Economics categories.
This empirical research methods course enables informed implementation of statistical procedures, giving rise to trustworthy evidence.
Dynamic Data Assimilation
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Author : Dinesh G. Harkut
language : en
Publisher: BoD – Books on Demand
Release Date : 2020-10-28
Dynamic Data Assimilation written by Dinesh G. Harkut and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-28 with Computers categories.
Data assimilation is a process of fusing data with a model for the singular purpose of estimating unknown variables. It can be used, for example, to predict the evolution of the atmosphere at a given point and time. This book examines data assimilation methods including Kalman filtering, artificial intelligence, neural networks, machine learning, and cognitive computing.
Cognitive Analytics Concepts Methodologies Tools And Applications
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2020-03-06
Cognitive Analytics Concepts Methodologies Tools And Applications written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-06 with Science categories.
Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries, including business and healthcare. It is necessary to develop specific software programs that can analyze and interpret large amounts of data quickly in order to ensure adequate usage and predictive results. Cognitive Analytics: Concepts, Methodologies, Tools, and Applications provides emerging perspectives on the theoretical and practical aspects of data analysis tools and techniques. It also examines the incorporation of pattern management as well as decision-making and prediction processes through the use of data management and analysis. Highlighting a range of topics such as natural language processing, big data, and pattern recognition, this multi-volume book is ideally designed for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, software engineers, IT specialists, and academicians.
Computational And Methodological Statistics And Biostatistics
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Author : Andriëtte Bekker
language : en
Publisher: Springer Nature
Release Date : 2020-08-10
Computational And Methodological Statistics And Biostatistics written by Andriëtte Bekker and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-10 with Medical categories.
In the statistical domain, certain topics have received considerable attention during the last decade or so, necessitated by the growth and evolution of data and theoretical challenges. This growth has invariably been accompanied by computational advancement, which has presented end users as well as researchers with the necessary opportunities to handle data and implement modelling solutions for statistical purposes. Showcasing the interplay among a variety of disciplines, this book offers pioneering theoretical and applied solutions to practice-oriented problems. As a carefully curated collection of prominent international thought leaders, it fosters collaboration between statisticians and biostatisticians and provides an array of thought processes and tools to its readers. The book thereby creates an understanding and appreciation of recent developments as well as an implementation of these contributions within the broader framework of both academia and industry. Computational and Methodological Statistics and Biostatistics is composed of three main themes: • Recent developments in theory and applications of statistical distributions;• Recent developments in supervised and unsupervised modelling;• Recent developments in biostatistics; and also features programming code and accompanying algorithms to enable readers to replicate and implement methodologies. Therefore, this monograph provides a concise point of reference for a variety of current trends and topics within the statistical domain. With interdisciplinary appeal, it will be useful to researchers, graduate students, and practitioners in statistics, biostatistics, clinical methodology, geology, data science, and actuarial science, amongst others.
Handbook Of Statistical Analysis And Data Mining Applications
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Author : Ken Yale
language : en
Publisher: Elsevier
Release Date : 2017-11-09
Handbook Of Statistical Analysis And Data Mining Applications written by Ken Yale and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-09 with Mathematics categories.
Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. - Includes input by practitioners for practitioners - Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models - Contains practical advice from successful real-world implementations - Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions - Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications
Advanced And Multivariate Statistical Methods
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Author : Craig A. Mertler
language : en
Publisher: Taylor & Francis
Release Date : 2016-10-24
Advanced And Multivariate Statistical Methods written by Craig A. Mertler and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-24 with Mathematics categories.
Ideal for non-math majors, Advanced and Multivariate Statistical Methods teaches students to interpret, present, and write up results for each statistical technique without overemphasizing advanced math. This highly applied approach covers the why, what, when and how of advanced and multivariate statistics in a way that is neither too technical nor too mathematical. Students also learn how to compute each technique using SPSS software. New to the Sixth Edition Instructor ancillaries are now available with the sixth edition. All SPSS directions and screenshots have been updated to Version 23 of the software. Student learning objectives have been added as a means for students to target their learning and for instructors to focus their instruction. Key words are reviewed and reinforced in the end of chapter material to ensure that students understand the vocabulary of advanced and multivariate statistics.
Statistics Methodologies And Applications In Modern Business
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Author : Pasquale De Marco
language : en
Publisher: Pasquale De Marco
Release Date : 2025-04-27
Statistics Methodologies And Applications In Modern Business written by Pasquale De Marco and has been published by Pasquale De Marco this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-27 with Business & Economics categories.
In today's data-driven business landscape, statistics have become an indispensable tool for organizations seeking to make informed decisions, solve complex problems, and gain a competitive edge. Statistics: Methodologies and Applications in Modern Business is a comprehensive guide that empowers professionals, students, and researchers with the knowledge and skills to effectively utilize statistical tools and techniques in a wide range of business contexts. This book takes a comprehensive approach to statistics, covering fundamental concepts, methodologies, and applications across various business domains. It begins by introducing the significance of statistics in modern business, emphasizing its role in understanding data, making informed decisions, and solving complex business problems. The book then delves into descriptive statistics, explaining how to summarize and present data effectively. Inferential statistics are also explored, providing a framework for drawing conclusions from data and making predictions. Moving beyond the basics, the book covers advanced statistical concepts such as probability distributions, hypothesis testing, and estimation. These topics are presented in a clear and accessible manner, with real-world examples and case studies to illustrate their practical relevance. Additionally, the book introduces nonparametric tests, time series analysis, and Bayesian statistics, providing readers with a well-rounded understanding of statistical methods. With its comprehensive coverage, engaging writing style, and abundance of practical examples, Statistics: Methodologies and Applications in Modern Business is an invaluable resource for anyone seeking to enhance their statistical literacy and apply statistical techniques to solve real-world business problems. It is an essential read for business professionals, students, and researchers seeking to stay competitive in today's data-driven marketplace. Key Features: * Comprehensive coverage of fundamental statistical concepts, methodologies, and applications * Engaging writing style and real-world examples to illustrate practical relevance * In-depth exploration of advanced statistical topics such as probability distributions, hypothesis testing, and estimation * Introduction to nonparametric tests, time series analysis, and Bayesian statistics * Exercises and case studies to reinforce understanding and application of statistical techniques Statistics: Methodologies and Applications in Modern Business is the ultimate guide for anyone seeking to harness the power of statistics to make informed business decisions and drive success. If you like this book, write a review on google books!
Advanced Statistical Methods In Data Science
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Author : Ding-Geng Chen
language : en
Publisher: Springer
Release Date : 2016-11-30
Advanced Statistical Methods In Data Science written by Ding-Geng Chen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-30 with Mathematics categories.
This book gathers invited presentations from the 2nd Symposium of the ICSA- CANADA Chapter held at the University of Calgary from August 4-6, 2015. The aim of this Symposium was to promote advanced statistical methods in big-data sciences and to allow researchers to exchange ideas on statistics and data science and to embraces the challenges and opportunities of statistics and data science in the modern world. It addresses diverse themes in advanced statistical analysis in big-data sciences, including methods for administrative data analysis, survival data analysis, missing data analysis, high-dimensional and genetic data analysis, longitudinal and functional data analysis, the design and analysis of studies with response-dependent and multi-phase designs, time series and robust statistics, statistical inference based on likelihood, empirical likelihood and estimating functions. The editorial group selected 14 high-quality presentations from this successful symposium and invited the presenters to prepare a full chapter for this book in order to disseminate the findings and promote further research collaborations in this area. This timely book offers new methods that impact advanced statistical model development in big-data sciences.