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New Statistical Developments in Data Science

SIS 2017, Florence, Italy, June 28-30

  • Alessandra Petrucci
  • Filomena Racioppi
  • Rosanna Verde

Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 288)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Complex Data Analytics

    1. Front Matter
      Pages 1-1
    2. A. Balzanella, E. Romano, Rosanna Verde, F. Fortuna, F. Maturo, S. A. Gattone et al.
      Pages 3-12
    3. Giancarlo Ragozini, Maria Prosperina Vitale, Giuseppe Giordano
      Pages 53-63
    4. Francesco Santelli, Francesco Palumbo, Giancarlo Ragozini
      Pages 77-89
    5. Amalia Vanacore, Maria Sole Pellegrino
      Pages 91-101
  3. Knowledge Based Methods

    1. Front Matter
      Pages 103-103
    2. Johan Koskinen, Chiara Broccatelli, Peng Wang, Garry Robins
      Pages 105-117
    3. Andrea Sottosanti, Denise Costantin, Denis Bastieri, Alessandra R. Brazzale
      Pages 135-148
    4. Federico M. Stefanini, Giulia Callegaro
      Pages 149-164
    5. M. Subbiah, R. Renuka Devi, M. Gallo, M. R. Srinivasan
      Pages 165-176
  4. Sampling Techniques for Big Data Exploration

    1. Front Matter
      Pages 177-177
    2. M. Simona Andreano, Roberto Benedetti, Federica Piersimoni, Paolo Postiglione, Giovanni Savio
      Pages 179-189
    3. Claudia De Vitiis, Alessio Guandalini, Francesca Inglese, Marco Dionisio Terribili
      Pages 203-217
  5. Data Science Methods for Social and Population Studies

    1. Front Matter
      Pages 247-247
    2. Paolo Balduzzi, Alessandro Rosina, Emiliano Sironi
      Pages 249-261
    3. Francesca Bassi, Leonardo Grilli, Omar Paccagnella, Carla Rampichini, Roberta Varriale
      Pages 263-274
    4. Marica Manisera, Rodolfo Metulini, Paola Zuccolotto
      Pages 305-318
    5. Isabella Morlini, Maristella Scorza
      Pages 319-328
    6. Righi Alessandra, Mauro M. Gentile, Domenico M. Bianco
      Pages 329-344
  6. Applying Data Science in Economics and Labour Market

    1. Front Matter
      Pages 345-345
    2. Alexander Agapitov, Irina Lakman, Zoya Maksimenko, Natalia Efimenko
      Pages 347-357
    3. Paolo Mariani, Andrea Marletta, Mariangela Zenga
      Pages 359-372
    4. Angelo Mazza, Antonio Punzo
      Pages 373-391
    5. Gennaro Punzo, Mariateresa Ciommi, Gaetano Musella, Rosalia Castellano
      Pages 393-406
    6. Viktoriya Voytsekhovska, Olivier Karl Butzbach
      Pages 407-417
  7. Mathematical Statistics for Data Science

    1. Front Matter
      Pages 419-419
    2. Roberto Fontana, Fabio Rapallo
      Pages 421-434
    3. Alessandro Lanteri, Mauro Maggioni, Stefano Vigogna
      Pages 447-456
    4. Valentina Mameli, Debora Slanzi, Irene Poli
      Pages 469-479

About these proceedings

Introduction

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.


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

Editors and affiliations

  • Alessandra Petrucci
    • 1
  • Filomena Racioppi
    • 2
  • Rosanna Verde
    • 3
  1. 1.Dipartimento di Statistica, Informatica, Applicazioni ‘G. Parenti’ (DiSIA)Università degli Studi di FirenzeFlorenceItaly
  2. 2.Dipartimento Scienze StatisticheSapienza Università di RomaRomeItaly
  3. 3.Dipartimento di Matematica e FisicaUniversità della Campania ‘Luigi Vanvitelli’CasertaItaly

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-21158-5
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-030-21157-8
  • Online ISBN 978-3-030-21158-5
  • Series Print ISSN 2194-1009
  • Series Online ISSN 2194-1017
  • Buy this book on publisher's site