Intuition refers to the ability to use nonconscious information for conscious decision making. The nonconscious element has predominantly been measured by its speed of operation and ease of application. Only a few scholarly attempts at behavioral measuring take nonconsciousness into account, and they use situations that do not represent the real world, which limits generalization. In my talk, I will present the results of my intuition measurement using a within-subject design with real investment opportunities that employ hidden images as nonconscious information to trigger intuition. My experiments were conducted entirely online from July to September 2021 in Europe and the United States. I will provide an overview of my current Bayesian analysis of 62,721 real-world investment decisions made by 657 subjects representing similar proportions of financiers, entrepreneurs, and non-entrepreneurs, all recruited via Prolific. I will also discuss additional ideas that could enrich our understanding of how to measure skills at using nonconscious information for conscious, real-world decision making. As such, my presentation will focus on my existing analytical results, my intentions for future analysis, and my plans for a new project, with the dual aims of sharing what my team and I have learned so far and receiving valuable early-stage suggestions for improvement and feedback from Applied Statistics Workshop participants. 

Where: CGIS Knafel Building, Room K354