Joint Summer School ERS-IASC, ECAS and SIS-CLADAG Clustering, Data Analysis and Visualization of Complex Data May 21-25, 2018, Catania (Italy)

The course is intended to achieve postgraduate training in special areas of statistics for both researchers and professional data analysts. The focus is on classification and clustering methods with particular emphasis on modern high-dimensional data sets (MHDS). MHDS have recently emerged because of the fast improvement in data acquisition, storage and processing. The availability of massive data sets are of large interest also in machine learning, data science and computer science. It applies in many contexts such as biological experiments, financial markets, astronomy, etc. Classification and clustering play a key role in this new paradigm to discover the inhomogeneous structure often underlying these data. Starting from basic concepts, the course will introduce the audience to novel techniques and software through extensive applications to real data.

More information available at http://www.clucla-summerschool.org/

News from the World of Statistics: November 2017

  • Workshops in India Draw Clinicians, Researchers for Software Training and Biostatistics Education
  • Symposium on Statistical Inference Gathers Professionals to Address Reproducibility in Research
  • OECD Releases New Publication Offering Guidance to Understanding Financial Accounts
  • BigSurv18 to Connect Survey Science, Big Data in October 2018
  • Senegal Statistics Community to Celebrate Mathematical Days
  • European Statistics Day Celebrated by Many
  • RSS Publishes New Educational Resources, Activities for Students and Guide for Legal Professionals
  • ICSA Seeks Proposals for Invited Sessions at 2018 Symposium
  • FENStatS Drafts Letter Supporting Former Greek Statistics Officials
  • Contribute News, Jobs to the World of Statistics

Joint Summer School ERS-IASC, ECAS and SIS-CLADAG Clustering, Data Analysis and Visualization of Complex Data May 21-25, 2018, Catania (Italy)

The course is intended to achieve postgraduate training in special areas of statistics for both researchers and professional data analysts. The focus is on classification and clustering methods with particular emphasis on modern high-dimensional data sets (MHDS). MHDS have recently emerged because of the fast improvement in data acquisition, storage and processing. The availability of massive data sets are of large interest also in machine learning, data science and computer science. It applies in many contexts such as biological experiments, financial markets, astronomy, etc. Classification and clustering play a key role in this new paradigm to discover the inhomogeneous structure often underlying these data. Starting from basic concepts, the course will introduce the audience to novel techniques and software through extensive applications to real data.

More information available at http://www.clucla-summerschool.org/

News from the World of Statistics: October 2017, Issue 2

  • Celebrate European Statistics Day on October 20
  • International Statistical Institute Releases Report on 61st World Statistics Conference
  • Statistica Sinica Issues Call for Submissions for Special Issue on Big Data in Environmental Studies
  • BigSurv18 to Connect Survey Science, Big Data in October 2018
  • October Issue of Significance Estimates, Examines the Amount of Plastic in the World’s Oceans
  • India to Host Conference on Statistical Methods in Finance
  • New Eurostat Publication is Statistical Portrait of Men and Women in Europe
  • Afrika Statistika Shares New Releases, Updates
  • IISA 2017 Annual Conference Set for December
  • Jamaica Statistics Symposium Just Days Away
  • Contribute News, Jobs to the World of Statistics

Kursu programma “European Courses in Advanced Statistics” piedāvā augsta līmeņa kursus “Statistical Disclosure Control for Official Statistics“, kas notiks 2018. gada 20.-22. februārī Francijā.

This three day course will introduce basic and advanced concepts of statistical disclosure control, privacy and confidentiality. The topics covered include the motivation of statistical disclosure control in terms of disclosure risk scenarios and types of disclosure risk; measuring disclosure risk for traditional outputs: microdata and tabular data; common methods of statistical disclosure control applications; the impact of statistical disclosure control methods on utility. In addition, we introduce differential privacy which is a definition arising in computer science which provides formal and quantifiable guarantees of disclosure risk. This definition is becoming more important to statistical agencies who are moving towards more advanced and online modes of data dissemination. The course also covers legal and ethical issues, examples of best practice and applications in statistical offices or health authorities, as well as workshops on differential privacy, anonymisation and controlled access and generating synthetic data.

This is an exciting and unique course bringing together experts around the world to deliver the latest developments in privacy and confidentiality which will be pitched at the post-graduate level and for those working at statistical agencies.

By the end of this course, participants will understand the motivation of statistical disclosure control and the issues in applying statistical disclosure control methods in order to protect the confidentiality of respondents. Participants should be able to evaluate and critique the different statistical disclosure control methods depending on the type of statistical output with respect to the amount of protection afforded and the impact on the utility of the protected data. Participants should understand the definition of differential privacy and how it can be used for guaranteeing the confidentiality of statistical data. Participants should be able to apply advanced methods of statistical disclosure control based on new platforms of data dissemination.

Informācija par kursiem