Techniques modernes d’enquête par échantillonnage et de données complexes

> English

Projet de recherche en collaboration (2020-2023)

This project’s goal is to modernize survey sampling methodology and official statistics by bridging the gap between modern statistical tools and classical survey sampling techniques. This is to address the problem that surfaces when researchers use convenient, uncontrolled big data sources which often fail to represent the target population of interest because of inherent selection biases. This research is important because Canada’s population is widely diverse, and survey data needs to be representative of our population. If industry, government and academia use biased data to make data-driven decisions, it can negatively impact Canadians in critical and sometimes unforeseen ways.

Chefs de projet :
David Haziza, Université de Montréal
Changbao Wu, Université de Waterloo

Collaborateurs :
Jean-François Beaumont, Statistique Canada
Audrey Béliveau, Université de Waterloo
Song Cai, Université Carleton
Jiahua Chen, Université de la Colombie-Britannique
Sixia Chen, Université d’Oklahoma
Camelia Goga, Université de France-Comté
Jae-Kwang Kim, Université Iowa State
Zilin Wang, Université Wilfrid Laurier
Puying Zhao, Université Yunnan

Comments are closed.