Statistics versus Data Science, Explanation versus Prediction.We’ll briefly provide perspective and tips for navigating through the following dynamic tensions: A crucial skill to build when engaging in this world is awareness of the dangers and pitfalls of various modeling approaches and the turf battles that continue to rage around the best ways to perform them.
This transports us into the central galaxy of statistical analysis and machine learning, with a dramatic increase in wonder, potential, and complexity. If we consider well-crafted, empathetic construction graphical displays to be the first level of data-driven storytelling, a natural candidate for the next level is effective fitting of models and subsequent communication of inferences.
This talk discusses how to make our visualization stories more compelling but also more understandable.Ģ:10-2:40Data Storytelling 2.0: Fitting Models Amidst the Stat Wars ––––––––––––––––––––– Russ Wolfinger. However, charts, graphs, infographics, and the narratives build with them can also be easily misinterpreted. Visualization is a powerful tool to make sense of data and to communicate insights and results to varied audience. In this talk I will survey examples of communicative visualization and the issues they raise, discuss research addressing those issues, and champion the emergence of a new discipline: data communication.ġ:40-2:10What You Design is Not What People See ––––––––––––––––––––––––––––––––––––– Alberto Cairo.
Such drastic changes in audience and application demand new approaches. But today most people experience visualization in a communicative setting, with visuals designed to deliver meaning, by mainstream media outlets like the New York Times. Visualization has focused for decades on helping experts discover meaning in their data.