Application-Driven Statistical Advancements
The advancement of academic statistics requires novel contributions to statistics in terms of new methodology. Such novelty often arises as a need for analytics of a real-world application presenting complexity not seen before. This area of statistical science aims to provide novel approaches to problems in the real world that are difficult for existing statistical frameworks to solve.
This interdisciplinary approach combines theoretical rigor with practical applicability, aiming to create impactful solutions across various domains. Developing software packages and tutorials that connect theoretical concepts with practical applications could be valuable. The application areas are diverse and could include spatial data, epidemiology, financial data, temporal data, health data and environmental data for example.