Roger Peng, University of Texas at Austin and
Stephanie Hicks, Johns Hopkins University
Tuesday, October 17th 11:00am
The Theory of Data Analysis is a multidimensional framework that underpins effective analytic practice. Beyond statistical thinking, the integration of design thinking emerges as a pivotal aspect in crafting effective solutions tailored to end-users. In this panel we will discuss the nuanced choices faced by data analysts, ranging from methodology selection to workflow design, each of which shapes he resulting analysis and user experience. We frame this role as that of a designer, guided by a set of fundamental principles. Additionally, we will delve into the pivotal concept of modeling analytic iteration, as outlined by John Tukey in 1977. Unlike traditional statistical theory, data analysts engage in dynamic decision-making based on observed data, necessitating structured guidance for these pivotal choices. Finally, we will scrutinize the critical domain of trust and reliability in data analysis. Join us for a comprehensive exploration of these facets as we discuss the evolving landscape of data analysis.