Applied Statistics and Policy Analysis Conference, 2019

Events

  • 05 September - 06 September 2019
  • Charles Sturt University, Wagga Wagga, Australia
  • Organiser: Data Science Research Unit (DSRU), School of Computing and Mathematics, Charles Sturt University
  • Event Details

The theme of ASPAC'19 is "Effective policy through the use of big data, accurate estimates and modern computing tools and statistical modelling".

Applied statistics and data science play a vital role in the analysis and evaluation of policies in various fields including social sciences, economics, health sciences, population studies etc. On the other hand, with society apparently expecting more and more from all three levels of government; it becomes increasingly important that both private and public policy should be based on reliable and up-to-date data that covers the important issues. This conference aims to promote research collaborations and exchange ideas between data scientists, applied statisticians and data modellers who will detail the latest innovations in research to gather and disseminate information from small to big data settings, and from policy analysts who will describe how they use existing information from increasing big data environments and indicate areas in which there need to be methodological and technological developments. Another aim is to establish connections between researchers at tertiary institutions and working in industry in Australia and overseas. This conference is organised by the Data Science Research Unit (DSRU) within the School of Computing and Mathematics at Charles Sturt University (CSU).

This conference is sponsored by the Australian Government’s Department of Infrastructure, Regional Development and Cities and the School of Computing and Mathematics and the Faculty of Business, Justice and Behavioural Sciences at CSU.
Topics of interest cover all aspects of statistics, data science and policy analysis methods. This may include, but it is not limited to:

Applied statistics and Bayesian modelling
Business statistics and forecasting
Computational statistics
Health statistics
Multivariate statistics
Sample surveys/methodology
Small area estimation
Social statistics

Artificial intelligence
Big data analytics
Business analytics
Data mining
Data science
Image processing
Microdata analysis
Microsimulation modelling

Business policy analysis
Natural resources management and ecological sustainability
Public policy
Policy analysis and evaluation
Social capital, social inclusion and economic indices
Socio-economic policy development - including the Aboriginal issues and policy research, etc.
Geospatial and environmental modelling
Agricultural modelling and policy

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