Overview
- Highlights key statistical methods and recent contributions to data science
- Shows how Statistics and Data Analysis techniques can support business operations and provide essential information for decision-making
- Promotes the development of a statistical culture among students and researchers in the Information Age
Part of the book series: Springer Proceedings in Mathematics & Statistics (PROMS, volume 288)
Included in the following conference series:
Conference proceedings info: SIS 2017.
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (35 papers)
-
Front Matter
-
Complex Data Analytics
-
Front Matter
-
-
Knowledge Based Methods
-
Front Matter
-
-
Sampling Techniques for Big Data Exploration
-
Front Matter
-
Other volumes
-
New Statistical Developments in Data Science
Keywords
- Data Science
- Big Data
- Data Analysis
- Knowledge Based Methods
- Complex Data Analytics
- Proceedings
- Machine Learning
- Information and Computer Science
- Optimization
- Pattern Recognition
- Open Data
- Relational and Complex Data
- Structured and no-structured Data
- Sampling Extraction
- Data Modeling
- Pattern Selection
- High Dimensional Data Quality Validation
- Dimensional Reduction
About this book
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 withhere. Lastly, it will help Statisticians and Data Scientists recognize their counterparts’ fundamental role.
Editors and Affiliations
About the editors
Alessandra Petrucci is Professor of Social Statistics at the University of Florence, where she is Head of the Department of Statistics, Computer Science, and Applications and a member of the Academic Senate. Dr. Petrucci holds a PhD in Applied Statistics. Her research interests include methods for survey sampling, spatial statistics, environmental statistics, multivariate analysis, and teaching evaluation. She has published a considerable number of papers in national and international journals and has been a member of many research projects and scientific committees for several national and international conferences. Dr. Petrucci is an elected member of International Statistical Institute (ISI) and a fellow of the Italian Statistical Society (SIS). She is a member of the Centro Camilo Dagum, Tuscan Interuniversity Centre – Advanced Statistics for Equitable and Sustainable Development.
Filomena Racioppi is Associate Professor of Demography in the Department of Statistics at Sapienza University of Rome, where she is on the Board of the PhD program in Statistical Sciences. She is a member of the Italian Association for Population Studies, the Italian Statistical Society (SIS), the European Association for Population Studies (EAPS), and the International Union for Scientific Studies of Population (IUSSP). She has been a member and/or coordinator of several national and international research projects. She was executive editor of Genus from 1999 to 2009 and a member of the scientific advisory board for Population Research and Policy Review. Currently she is on the scientific board of Genus and serves as a reviewer for several demographic international journals. Dr. Racioppi’s research areas have included, among others, reproductive behaviors, applied and business demography, active ageing and age management, and gender issues during the life course.
Rosanna Verde is Professor of Statistics in the Department of Mathematicsand Physics at the University of Campania Luigi Vanvitelli, where she is coordinator of the Bachelor’s degree in Data Analytics. She is also on the Board of the PhD program in Social and Statistical Sciences at the University of Naples. Dr. Verde is a member of several international statistical associations and she is on the scientific board of SIS Group on Statistics and Data Science. She is associate editor of Statistical Methods & Application journal. She was an expert evaluator for the European Programme IST. She has coordinated various national and regional projects, and she has also participated in European projects. She was guest researcher and visiting professor at several foreign universities and research centres. Her main fields of research are: classification, symbolic data analysis, data stream analysis, and functional data analysis. She is a co-author of more than 100 papers in journals and in proceedings of international conferences.
Bibliographic Information
Book Title: New Statistical Developments in Data Science
Book Subtitle: SIS 2017, Florence, Italy, June 28-30
Editors: Alessandra Petrucci, Filomena Racioppi, Rosanna Verde
Series Title: Springer Proceedings in Mathematics & Statistics
DOI: https://doi.org/10.1007/978-3-030-21158-5
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-21157-8Published: 21 August 2019
Softcover ISBN: 978-3-030-21160-8Published: 21 August 2020
eBook ISBN: 978-3-030-21158-5Published: 20 August 2019
Series ISSN: 2194-1009
Series E-ISSN: 2194-1017
Edition Number: 1
Number of Pages: XIV, 479
Number of Illustrations: 38 b/w illustrations, 58 illustrations in colour
Topics: Statistics and Computing/Statistics Programs, Computational Mathematics and Numerical Analysis, Business Finance, Statistics for Business, Management, Economics, Finance, Insurance, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences