The Luxembourg Statistical Society would like to invite you to the talk by Monica Pratesi on “Towards a framework to harness data by citizens: the Istat experience”. The talk will take place on Monday 17^th April at 12:00 PM in virtual mode.

Monica Pratesi is Director of the Department for Statistical Production, Istat, Italian National Institute of Statistics

Abstract

Big data, smart statistics, digital administrative data, and citizens are inseparable: from smartphones, meters, fridges and cars to internet platforms, the data of most digital technologies is citizen data, that is the data of the citizens and on citizens.

Their importance and their involvement ask for a thorough rethinking of the relations between the citizens and the production of official statistics. In the session we will focus on examples of the reuse of data generated by citizens on themselves (in processes like using services, making telephone calls or when they populate administrative archives during their lives as students, workers, retired persons etc.) to produce Official Statistics. Examples will use the statistical production process from the Permanent Population and Households Census, from the integration process of utility data files (e.g. electricity, gas) in the design of different activities, like for instance the Household Energy Consumption Survey or data collection on violence against women and on discrimination (LGBTQ+ population, Roma and homeless) conducted in cooperation with civil society organizations, also touching upon the issue of the reuse of privately-held-data in official statistics.

Practical information

Date: 17 April 2023
Time: 12:00-13:00
Place: online
Fee: free
Registration: please register by sending an email to Christophe Ley (Société Statistique Luxembourgeoise)

The Luxembourg Statistical Society would like to invite you to the talk by Prof. Christophe Ley on “Statistical Modelling and Data Science”. The talk will take place on Thursday 20^th April at 17:30 PM in person mode. It will be in the room 3.330 of the Maison du Savoir on the University Campus Belval.

Christophe Ley joined the Department of Mathematics at the University of Luxembourg in November 2021 as Associate Professor. He is an applied mathematician working in the field of statistics/data science, with a strong taste for interdisciplinary work. Before joining the University of Luxembourg, he was Associate Professor at Ghent University in Belgium. He obtained his PhD from the Université libre de Bruxelles in 2010, where he had also studied except for the first year, which he did at the University of Luxembourg during its first year of existence in 2003-2004.

He is President of the Luxembourg Statistical Society, President of the European organisation for Advanced Courses in Statistics (ECAS), and Leader of the international network S-TRAINING (new data science methods for sports analytics and sports medicine). Among his achievements are the Prix Marie-Jeanne Laurent-Duhamel, rewarding the best PhD thesis in Statistics over a period of 3 years among all French-speaking universities world-wide, and an Elected Membership at the International Statistical Institute. 

He leads the research team MIDAS which stands for Modelling – Interdisciplinary – Data (Science) – Applied – Statistics. The team’s aim is to develop innovative statistical and machine learning procedures based on new mathematical and computational tools to tackle the challenges posed by modern days’ increasingly complex and large data sets.

Abstract

Since the turn of the millenium, technological innovations have allowed the collection and storage of increasingly complex and large data sets, a situation that has in turn spurred significant advances in such domains as medicine, meteorology, renewable energies, engineering, sports, social sciences, and many more. Most of these scientific advances are grounded on strong mathematical foundations – see for instance the variety of epidemiological models required to understand the COVID-19 spread, or the statistical theories underpinning clinical studies. In his talk, Prof. Christophe Ley will provide a friendly overview on statistical modelling and data science, two important themes of his own research and that of his research team. He will describe modern challenges and, in particular, focus on research he wishes to undertake in the coming years.

Practical information

Date: 20 April 2023
Time: 17:30-20:00
Place: room 3.330, Maison du Savoir (Belval campus)
Fee: free
Registration: please register by sending an email to Christophe Ley (Société Statistique Luxembourgeoise)

The Luxembourg Statistical Society would like to invite you to the talk by Prof. Sarah Gelper on “Estimating the Effect of Second Screening on TV Viewing using Mobile Diaries”. The talk will take place on Thursday 23^rd February at 12:30 PM in hybrid mode. If you attend it in person, it will be in the room on the first floor of the Maison du Nombre, MNO-E01-0146030, on the University Campus Belval.

Sarah Gelper is Associate Professor in Business Analytics with a Specialization in Marketing Analytics at Université du Luxembourg.

Abstract

People often use second devices, such as their mobile or tablet, while watching TV. Such « second screening » might enhance engagement and increase viewership but also risks distracting viewers and reducing interest in the show. Estimating the effect of second screening on repeat viewing is challenging for three reasons. (1) We need to observe behavior on two different devices (the data challenge); (2) the effect of second screening might vary with viewer and show characteristics (the heterogeneity challenge); and (3) second screening is highly endogenous behavior (the endogeneity challenge). This paper leverages large-scale individual-level data from mobile diaries of 1,702 US TV viewers on 2,755 primetime TV shows over 3-6 weeks in which viewers report both viewing and second screening. The data are augmented to account for a broad set of marketing influences such as show communications and promos. We characterize heterogeneity by four latent viewer classes (heavy viewers, sports enthusiasts, sitcom viewers, and light viewers) and use a causal forest analysis to estimate the heterogeneous effects of second screening on repeat viewing. Despite the possible risk of distraction, second screening does not harm actual TV viewing, and this effect is robust over various types of second screening activities and across viewer segments. Second screening impacts attitudes more than behaviors – unlike actual viewing, stated viewing intentions are affected right after the second screening experience. Specifically, viewing intentions increase when people use a second screen to communicate about the show, but decrease when they use the second screen for show-unrelated activities.

Practical information

Date: 23 February 2023
Time: 13:00-14:00
Place: room MNO-E01-0146030 (Belval campus)
Fee: free
Registration: please register by sending an email to Christophe Ley (Société Statistique Luxembourgeoise)

À l’occasion de la Journée mondiale de la statistique, nous vous invitons à découvrir comment l’intelligence artificielle pénètre dans des domaines aussi variés que les diagnostics médicaux, la physique des particules ou encore l’astronomie.

La leçon inaugurale sera donnée par le président de la Société Statistique Luxembourgeoise et professeur en statistique appliquée à l’Uni.lu,
Dr Christophe Ley.

Horaire : Samedi 12 octobre 2022 de 14h00 à 18h00 au Luxembourg Science Center

Adresse: Luxembourg Science Center – 1 rue John E. Dolibois, L-4620 Differdange

Attention: places limitées!

Inscriptions : Pour participer, veuillez envoyer un email à info@statec.etat.lu.

Luxembourg Statistical Society has the pleasure to invite you to our second event of our society this year – an hybrid talk by Prof. Yannick Baraud (Department of Mathematics, Université du Luxembourg, Luxembourg).

Abstract

In this talk, Prof. Yannick Baraud will present some of the research topics of the SanDAL* group. One of them is the search of a universal estimation procedure, i.e. a procedure which is applicable to all statistical models and automatically leads to an estimator of the distribution of the data that is both optimal and stable to the presence of outliers among the sample. We shall see how mathematics allow us to analyze the non-asymptotic properties of this new type of estimator, i.e. when the number of data is fixed and not necessarily large. Finally, we will illustrate its performance on some simulations by comparing it to some classical estimators.

*SanDAL is a Chair in Mathematical Statistics and Data Science at the University of Luxembourg which is funded by the European Union’s Horizon 2020 programme.

Practical information

Date: 28 March 2022
Time: 18:00 – 19:00
Place: online and in person
Fee: free
Registration: mandatory at Luxstat