UIUC Quant Brownbag

Representational Measurement Theory (RMT) is a framework in measurement science that formalizes the relationships between abstract concepts and their empirical counterparts. It involves mapping empirical attributes onto numerical representations while preserving the inherent structure and relationships of the original attributes. RMT also enables the understanding and discovery of scientific laws and principles, even when direct quantification is challenging. This talk offers an accessible introduction to the principles of RMT and the types of insights it can provide from existing data. We will discuss both actual and potential applications, encouraging researchers to incorporate RMT into their own work. By exploring the concept of “meaningful scientific laws”, we will demonstrate how RMT can help us identify these laws in psychological science (at least in principle). This talk showcases RMT’s potential to yield deeper discoveries, opening new avenues for research and understanding in various scientific fields.