Recent Developments In Statistics And Data Science

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New Advances in Statistics and Data Science

Ding-Geng Chen,Zhezhen Jin,Gang Li,Yi Li,Aiyi Liu,Yichuan Zhao
New Advances in Statistics and Data Science Book PDF

Author : Ding-Geng Chen,Zhezhen Jin,Gang Li,Yi Li,Aiyi Liu,Yichuan Zhao
Publisher : Springer
Page : 348 pages
File Size : 53,7 Mb
Release : 2018-01-17
Category : Mathematics
ISBN : 9783319694160

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New Advances in Statistics and Data Science by Ding-Geng Chen,Zhezhen Jin,Gang Li,Yi Li,Aiyi Liu,Yichuan Zhao Pdf

This book is comprised of the presentations delivered at the 25th ICSA Applied Statistics Symposium held at the Hyatt Regency Atlanta, on June 12-15, 2016. This symposium attracted more than 700 statisticians and data scientists working in academia, government, and industry from all over the world. The theme of this conference was the “Challenge of Big Data and Applications of Statistics,” in recognition of the advent of big data era, and the symposium offered opportunities for learning, receiving inspirations from old research ideas and for developing new ones, and for promoting further research collaborations in the data sciences. The invited contributions addressed rich topics closely related to big data analysis in the data sciences, reflecting recent advances and major challenges in statistics, business statistics, and biostatistics. Subsequently, the six editors selected 19 high-quality presentations and invited the speakers to prepare full chapters for this book, which showcases new methods in statistics and data sciences, emerging theories, and case applications from statistics, data science and interdisciplinary fields. The topics covered in the book are timely and have great impact on data sciences, identifying important directions for future research, promoting advanced statistical methods in big data science, and facilitating future collaborations across disciplines and between theory and practice.

Practical Statistics for Data Scientists

Peter Bruce,Andrew Bruce
Practical Statistics for Data Scientists Book PDF

Author : Peter Bruce,Andrew Bruce
Publisher : "O'Reilly Media, Inc."
Page : 395 pages
File Size : 47,6 Mb
Release : 2017-05-10
Category : Computers
ISBN : 9781491952917

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Practical Statistics for Data Scientists by Peter Bruce,Andrew Bruce Pdf

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data

Recent Developments in Statistics and Data Science

Regina Bispo,Lígia Henriques-Rodrigues,Russell Alpizar-Jara,Miguel de Carvalho
Recent Developments in Statistics and Data Science Book PDF

Author : Regina Bispo,Lígia Henriques-Rodrigues,Russell Alpizar-Jara,Miguel de Carvalho
Publisher : Springer Nature
Page : 364 pages
File Size : 51,7 Mb
Release : 2022-11-28
Category : Mathematics
ISBN : 9783031127663

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Recent Developments in Statistics and Data Science by Regina Bispo,Lígia Henriques-Rodrigues,Russell Alpizar-Jara,Miguel de Carvalho Pdf

This volume presents a collection of twenty-five peer-reviewed articles carefully selected from the contributions presented at the XXV Congress of the Portuguese Statistical Society (2021). Containing state-of-the-art developments in theoretical and applied statistics, the book will be accessible to readers with a background in mathematics and statistics, but will also be of interest to researchers from other scientific disciplines (e.g., biology, economics, medicine), who will find a broad range of relevant applications.

Recent Developments in Data Science and Business Analytics

Madjid Tavana,Srikanta Patnaik
Recent Developments in Data Science and Business Analytics Book PDF

Author : Madjid Tavana,Srikanta Patnaik
Publisher : Springer
Page : 505 pages
File Size : 43,5 Mb
Release : 2018-03-27
Category : Business & Economics
ISBN : 9783319727455

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Recent Developments in Data Science and Business Analytics by Madjid Tavana,Srikanta Patnaik Pdf

This edited volume is brought out from the contributions of the research papers presented in the International Conference on Data Science and Business Analytics (ICDSBA- 2017), which was held during September 23-25 2017 in ChangSha, China. As we all know, the field of data science and business analytics is emerging at the intersection of the fields of mathematics, statistics, operations research, information systems, computer science and engineering. Data science and business analytics is an interdisciplinary field about processes and systems to extract knowledge or insights from data. Data science and business analytics employ techniques and theories drawn from many fields including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition, visualization, descriptive analytics, predictive analytics, prescriptive analytics, uncertainty modeling, big data, data warehousing, data compression, computer programming, business intelligence, computational intelligence, and high performance computing among others. The volume contains 55 contributions from diverse areas of Data Science and Business Analytics, which has been categorized into five sections, namely: i) Marketing and Supply Chain Analytics; ii) Logistics and Operations Analytics; iii) Financial Analytics. iv) Predictive Modeling and Data Analytics; v) Communications and Information Systems Analytics. The readers shall not only receive the theoretical knowledge about this upcoming area but also cutting edge applications of this domains.

Advanced Statistical Methods in Data Science

Ding-Geng Chen,Jiahua Chen,Xuewen Lu,Grace Y. Yi,Hao Yu
Advanced Statistical Methods in Data Science Book PDF

Author : Ding-Geng Chen,Jiahua Chen,Xuewen Lu,Grace Y. Yi,Hao Yu
Publisher : Springer
Page : 0 pages
File Size : 54,6 Mb
Release : 2018-07-05
Category : Mathematics
ISBN : 9811096627

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Advanced Statistical Methods in Data Science by Ding-Geng Chen,Jiahua Chen,Xuewen Lu,Grace Y. Yi,Hao Yu Pdf

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.

Trends of Data Science and Applications

Siddharth Swarup Rautaray,Phani Pemmaraju,Hrushikesha Mohanty
Trends of Data Science and Applications Book PDF

Author : Siddharth Swarup Rautaray,Phani Pemmaraju,Hrushikesha Mohanty
Publisher : Springer Nature
Page : 341 pages
File Size : 48,6 Mb
Release : 2021-03-21
Category : Computers
ISBN : 9789813368156

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Trends of Data Science and Applications by Siddharth Swarup Rautaray,Phani Pemmaraju,Hrushikesha Mohanty Pdf

This book includes an extended version of selected papers presented at the 11th Industry Symposium 2021 held during January 7–10, 2021. The book covers contributions ranging from theoretical and foundation research, platforms, methods, applications, and tools in all areas. It provides theory and practices in the area of data science, which add a social, geographical, and temporal dimension to data science research. It also includes application-oriented papers that prepare and use data in discovery research. This book contains chapters from academia as well as practitioners on big data technologies, artificial intelligence, machine learning, deep learning, data representation and visualization, business analytics, healthcare analytics, bioinformatics, etc. This book is helpful for the students, practitioners, researchers as well as industry professional.

New Statistical Developments in Data Science

Alessandra Petrucci,Filomena Racioppi,Rosanna Verde
New Statistical Developments in Data Science Book PDF

Author : Alessandra Petrucci,Filomena Racioppi,Rosanna Verde
Publisher : Springer Nature
Page : 479 pages
File Size : 52,6 Mb
Release : 2019-08-20
Category : Computers
ISBN : 9783030211585

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New Statistical Developments in Data Science by Alessandra Petrucci,Filomena Racioppi,Rosanna Verde Pdf

This volume collects the extended versions of papers presented at the SIS Conference “Statistics and Data Science: new challenges, new generations”, held in Florence, Italy on June 28-30, 2017. Highlighting the central role of statistics and data analysis methods in the era of Data Science, the contributions offer an essential overview of the latest developments in various areas of statistics research. The 35 contributions have been divided into six parts, each of which focuses on a core area contributing to “Data Science”. The book covers topics including strong statistical methodologies, Bayesian approaches, applications in population and social studies, studies in economics and finance, techniques of sample design and mathematical statistics. Though the book is mainly intended for researchers interested in the latest frontiers of Statistics and Data Analysis, it also offers valuable supplementary material for students of the disciplines dealt with here. Lastly, it will help Statisticians and Data Scientists recognize their counterparts’ fundamental role.

Recent Developments in Statistics and Data Science

Yusheng Li,Qizhong Lin
Recent Developments in Statistics and Data Science Book PDF

Author : Yusheng Li,Qizhong Lin
Publisher : Unknown
Page : 0 pages
File Size : 41,7 Mb
Release : 2022
Category : Biometry
ISBN : 8303112767

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Recent Developments in Statistics and Data Science by Yusheng Li,Qizhong Lin Pdf

This volume presents a collection of twenty-five peer-reviewed articles carefully selected from the contributions presented at the XXV Congress of the Portuguese Statistical Society (2021). Containing state-of-the-art developments in theoretical and applied statistics, the book will be accessible to readers with a background in mathematics and statistics, but will also be of interest to researchers from other scientific disciplines (e.g., biology, economics, medicine), who will find a broad range of relevant applications.

Statistics for Data Science

James D. Miller
Statistics for Data Science Book PDF

Author : James D. Miller
Publisher : Packt Publishing Ltd
Page : 279 pages
File Size : 48,6 Mb
Release : 2017-11-17
Category : Computers
ISBN : 9781788295345

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Statistics for Data Science by James D. Miller Pdf

Get your statistics basics right before diving into the world of data science About This Book No need to take a degree in statistics, read this book and get a strong statistics base for data science and real-world programs; Implement statistics in data science tasks such as data cleaning, mining, and analysis Learn all about probability, statistics, numerical computations, and more with the help of R programs Who This Book Is For This book is intended for those developers who are willing to enter the field of data science and are looking for concise information of statistics with the help of insightful programs and simple explanation. Some basic hands on R will be useful. What You Will Learn Analyze the transition from a data developer to a data scientist mindset Get acquainted with the R programs and the logic used for statistical computations Understand mathematical concepts such as variance, standard deviation, probability, matrix calculations, and more Learn to implement statistics in data science tasks such as data cleaning, mining, and analysis Learn the statistical techniques required to perform tasks such as linear regression, regularization, model assessment, boosting, SVMs, and working with neural networks Get comfortable with performing various statistical computations for data science programmatically In Detail Data science is an ever-evolving field, which is growing in popularity at an exponential rate. Data science includes techniques and theories extracted from the fields of statistics; computer science, and, most importantly, machine learning, databases, data visualization, and so on. This book takes you through an entire journey of statistics, from knowing very little to becoming comfortable in using various statistical methods for data science tasks. It starts off with simple statistics and then move on to statistical methods that are used in data science algorithms. The R programs for statistical computation are clearly explained along with logic. You will come across various mathematical concepts, such as variance, standard deviation, probability, matrix calculations, and more. You will learn only what is required to implement statistics in data science tasks such as data cleaning, mining, and analysis. You will learn the statistical techniques required to perform tasks such as linear regression, regularization, model assessment, boosting, SVMs, and working with neural networks. By the end of the book, you will be comfortable with performing various statistical computations for data science programmatically. Style and approach Step by step comprehensive guide with real world examples

Computational Statistics in Data Science

Richard A. Levine,Walter W. Piegorsch,Hao Helen Zhang,Thomas C. M. Lee
Computational Statistics in Data Science Book PDF

Author : Richard A. Levine,Walter W. Piegorsch,Hao Helen Zhang,Thomas C. M. Lee
Publisher : John Wiley & Sons
Page : 672 pages
File Size : 41,7 Mb
Release : 2022-03-23
Category : Mathematics
ISBN : 9781119561088

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Computational Statistics in Data Science by Richard A. Levine,Walter W. Piegorsch,Hao Helen Zhang,Thomas C. M. Lee Pdf

Ein unverzichtbarer Leitfaden bei der Anwendung computergestützter Statistik in der modernen Datenwissenschaft In Computational Statistics in Data Science präsentiert ein Team aus bekannten Mathematikern und Statistikern eine fundierte Zusammenstellung von Konzepten, Theorien, Techniken und Praktiken der computergestützten Statistik für ein Publikum, das auf der Suche nach einem einzigen, umfassenden Referenzwerk für Statistik in der modernen Datenwissenschaft ist. Das Buch enthält etliche Kapitel zu den wesentlichen konkreten Bereichen der computergestützten Statistik, in denen modernste Techniken zeitgemäß und verständlich dargestellt werden. Darüber hinaus bietet Computational Statistics in Data Science einen kostenlosen Zugang zu den fertigen Einträgen im Online-Nachschlagewerk Wiley StatsRef: Statistics Reference Online. Außerdem erhalten die Leserinnen und Leser: * Eine gründliche Einführung in die computergestützte Statistik mit relevanten und verständlichen Informationen für Anwender und Forscher in verschiedenen datenintensiven Bereichen * Umfassende Erläuterungen zu aktuellen Themen in der Statistik, darunter Big Data, Datenstromverarbeitung, quantitative Visualisierung und Deep Learning Das Werk eignet sich perfekt für Forscher und Wissenschaftler sämtlicher Fachbereiche, die Techniken der computergestützten Statistik auf einem gehobenen oder fortgeschrittenen Niveau anwenden müssen. Zudem gehört Computational Statistics in Data Science in das Bücherregal von Wissenschaftlern, die sich mit der Erforschung und Entwicklung von Techniken der computergestützten Statistik und statistischen Grafiken beschäftigen.

Recent Advances in Data Science

Henry Han,Tie Wei,Wenbin Liu,Fei Han
Recent Advances in Data Science Book PDF

Author : Henry Han,Tie Wei,Wenbin Liu,Fei Han
Publisher : Springer Nature
Page : 295 pages
File Size : 43,8 Mb
Release : 2020-09-28
Category : Computers
ISBN : 9789811587603

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Recent Advances in Data Science by Henry Han,Tie Wei,Wenbin Liu,Fei Han Pdf

This book constitutes selected papers of the ​Third International Conference on Data Science, Medicine and Bioinformatics, IDMB 2019, held in Nanning, China, in June 2019. The 19 full papers and 1 short paper were carefully reviewed and selected from 93 submissions. The papers are organized according to the following topical sections: business data science: fintech, management, and analytics.- health and biological data science.- novel data science theory and applications.

New Statistical Developments in Data Science

Società italiana di statistica. Riunione scientifica
New Statistical Developments in Data Science Book PDF

Author : Società italiana di statistica. Riunione scientifica
Publisher : Unknown
Page : 128 pages
File Size : 46,6 Mb
Release : 2019
Category : Statistics
ISBN : 3030211592

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New Statistical Developments in Data Science by Società italiana di statistica. Riunione scientifica Pdf

This volume collects the extended versions of papers presented at the SIS Conference "Statistics and Data Science: new challenges, new generations", held in Florence, Italy on June 28-30, 2017. Highlighting the central role of statistics and data analysis methods in the era of Data Science, the contributions offer an essential overview of the latest developments in various areas of statistics research. The 35 contributions have been divided into six parts, each of which focuses on a core area contributing to "Data Science". The book covers topics including strong statistical methodologies, Bayesian approaches, applications in population and social studies, studies in economics and finance, techniques of sample design and mathematical statistics. Though the book is mainly intended for researchers interested in the latest frontiers of Statistics and Data Analysis, it also offers valuable supplementary material for students of the disciplines dealt with here. Lastly, it will help Statisticians and Data Scientists recognize their counterparts' fundamental role.

Advances in Data Science

Ilke Demir,Yifei Lou,Xu Wang,Kathrin Welker
Advances in Data Science Book PDF

Author : Ilke Demir,Yifei Lou,Xu Wang,Kathrin Welker
Publisher : Springer Nature
Page : 374 pages
File Size : 51,9 Mb
Release : 2021-12-03
Category : Mathematics
ISBN : 9783030798918

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Advances in Data Science by Ilke Demir,Yifei Lou,Xu Wang,Kathrin Welker Pdf

This volume highlights recent advances in data science, including image processing and enhancement on large data, shape analysis and geometry processing in 2D/3D, exploration and understanding of neural networks, and extensions to atypical data types such as social and biological signals. The contributions are based on discussions from two workshops under Association for Women in Mathematics (AWM), namely the second Women in Data Science and Mathematics (WiSDM) Research Collaboration Workshop that took place between July 29 and August 2, 2019 at the Institute for Computational and Experimental Research in Mathematics (ICERM) in Providence, Rhode Island, and the third Women in Shape (WiSh) Research Collaboration Workshop that took place between July 16 and 20, 2018 at Trier University in Robert-Schuman-Haus, Trier, Germany. These submissions, seeded by working groups at the conference, form a valuable source for readers who are interested in ideas and methods developed in interdisciplinary research fields. The book features ideas, methods, and tools developed through a broad range of domains, ranging from theoretical analysis on graph neural networks to applications in health science. It also presents original results tackling real-world problems that often involve complex data analysis on large multi-modal data sources.

Data Science

Francesco Palumbo,Angela Montanari,Maurizio Vichi
Data Science Book PDF

Author : Francesco Palumbo,Angela Montanari,Maurizio Vichi
Publisher : Springer
Page : 342 pages
File Size : 42,5 Mb
Release : 2017-07-05
Category : Mathematics
ISBN : 331955722X

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Data Science by Francesco Palumbo,Angela Montanari,Maurizio Vichi Pdf

This edited volume on the latest advances in data science covers a wide range of topics in the context of data analysis and classification. In particular, it includes contributions on classification methods for high-dimensional data, clustering methods, multivariate statistical methods, and various applications. The book gathers a selection of peer-reviewed contributions presented at the Fifteenth Conference of the International Federation of Classification Societies (IFCS2015), which was hosted by the Alma Mater Studiorum, University of Bologna, from July 5 to 8, 2015.

Data Science: New Issues, Challenges and Applications

Gintautas Dzemyda,Jolita Bernatavičienė,Janusz Kacprzyk
Data Science New Issues Challenges and Applications Book PDF

Author : Gintautas Dzemyda,Jolita Bernatavičienė,Janusz Kacprzyk
Publisher : Springer Nature
Page : 325 pages
File Size : 41,5 Mb
Release : 2020-02-13
Category : Computers
ISBN : 9783030392505

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Data Science: New Issues, Challenges and Applications by Gintautas Dzemyda,Jolita Bernatavičienė,Janusz Kacprzyk Pdf

This book contains 16 chapters by researchers working in various fields of data science. They focus on theory and applications in language technologies, optimization, computational thinking, intelligent decision support systems, decomposition of signals, model-driven development methodologies, interoperability of enterprise applications, anomaly detection in financial markets, 3D virtual reality, monitoring of environmental data, convolutional neural networks, knowledge storage, data stream classification, and security in social networking. The respective papers highlight a wealth of issues in, and applications of, data science. Modern technologies allow us to store and transfer large amounts of data quickly. They can be very diverse - images, numbers, streaming, related to human behavior and physiological parameters, etc. Whether the data is just raw numbers, crude images, or will help solve current problems and predict future developments, depends on whether we can effectively process and analyze it. Data science is evolving rapidly. However, it is still a very young field. In particular, data science is concerned with visualizations, statistics, pattern recognition, neurocomputing, image analysis, machine learning, artificial intelligence, databases and data processing, data mining, big data analytics, and knowledge discovery in databases. It also has many interfaces with optimization, block chaining, cyber-social and cyber-physical systems, Internet of Things (IoT), social computing, high-performance computing, in-memory key-value stores, cloud computing, social computing, data feeds, overlay networks, cognitive computing, crowdsource analysis, log analysis, container-based virtualization, and lifetime value modeling. Again, all of these areas are highly interrelated. In addition, data science is now expanding to new fields of application: chemical engineering, biotechnology, building energy management, materials microscopy, geographic research, learning analytics, radiology, metal design, ecosystem homeostasis investigation, and many others.