When seeing is learning: dynamic and interactive visualizations to teach statistical concepts

Citation: Moreau D (2015) When seeing is learning: dynamic and interactive visualizations to teach statistical concepts. Front. Psychol. 6:342. When Seeing is Learning: Dynamic and Interactive Visualizations to Teach Statistical Concepts " So, how would I use statistics in psychological research? First of all, descriptively. " – Jacob Cohen (1990), p. 1310. Jacob Cohen, one of the greatest statisticians of the twentieth century, reflected upon a problem many students of introductory statistics courses can relate to: the benefit of clear visual representations to understand statistical properties. Naturally, Cohen was not the first to touch upon this idea; in fact, he was echoing another exceptional statistician of the last century, John Tukey, who had emphasized the necessity of depicting data visually (Tukey, 1977). Decades later, this idea is still very contemporary—technologies have evolved, computing power has soared, but the perplexing nature of data analysis remains, especially for young scientists (Watts, 1991; Garfield and Ben-Zvi, 2007). What advances in computing allow, however, is a fresh approach to circumvent the problem. Modern technologies offer an impressive panel of tools and support to teach statistics, in and outside the classroom. It is now possible for students to dynamically interact with their data, in order to understand the relative contribution of individual data points, variables, or parameters. For example , they can fairly easily introduce one data point at a time in an analysis and monitor how each observation refines the underlying model. Or observe how changes in one parameter result in differences in power calculations (Figure 1). Students can also access fairly abstract concepts such as randomness or sampling in a glimpse. Moreover, these advances come at a time when statistics is becoming a seductive and appealing field to students and the general public. In the New York Times and the Wall Street Journal, at Google and Facebook, the message is clear: statistics is sexy. Equally revealing, Hans Rosling, in a riveting and broadly-praised talk, advises not to be ashamed to say you are a statistician at a dinner party (Rosling, 2010). We have come a long way. Yet how can we allow more students to grasp the critical concepts required to become statistically literate and apply data analysis methods adequately in current and future research programs? Many suggestions have been made, and this special research topic provides additional fascinating leads. In my opinion, one of the answers lies in the diversification of teaching …