Eurostat webinars for young statisticians open to EMOS
The objective of this webinar series is to equip participants with cutting-edge knowledge and practical skills in the application of advanced techniques and tools to enhance the quality, accuracy, and relevance of official statistics. Each session focuses on a specific area, providing a comprehensive understanding of machine learning, geospatial analysis, user needs evaluation, data integration, privacy enhancement, and the use of JDemetra for seasonal adjustments. By the end of the series, attendees will be well-versed in modern methodologies that can significantly improve statistical practices and outcomes in their respective organizations.
These webinars are organised under the European Statistical Training Programme (ESTP); they are an integral part of the EMOS webinar series.
| Webinar | Presenter |
|---|---|
Integrating data from multiple sources (used methods and tools) Discover the methods and tools used for combining data from diverse sources, enhancing the comprehensiveness and accuracy of official statistics. | Ton de Waal, Arnout van Delden |
How to gather and evaluate user needs in official statistics Understand methodologies and best practices for identifying and assessing user needs to improve the relevance and usability of official statistical data. | Sascha Oliver Rusch |
JDemetra Basics Get an introduction to JDemetra, a tool used for seasonal adjustment of time series data in official statistics, covering its fundamental features and functionalities | Anna Smyk |
Privacy Enhancing Technologies for Official Statistics Delve into technologies designed to protect privacy in the collection, processing, and dissemination of official statistics, ensuring data confidentiality. | Dr Peter-Paul de Wolf |
Geospatial Analysis Learn about geospatial analysis techniques for analyzing and visualizing spatial data, aiding in the interpretation and presentation of official statistics. | Miroslaw Migacz Amelia Wardzinska-Sharif |
Machine Learning for Official Statistics Explore the use of machine learning techniques such as classification, clustering, and predictive modeling to enhance the accuracy and efficiency of official statistics. | Ahmet Emin Tatar |