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Introducing an online application for estimation plots in a New Statistics framework #1284

A common step in quantitative research into language learning is the reliance on null-hypothesis statistical significance testing (NHST) to show the effectiveness or otherwise of different treatments for groups. However, as has been well-documented, multiple problems exist with this approach (see: The American Statistician, 2019, Volume 73, sup1). To move beyond the limitations of NHST, Cumming (2012, 2014) introduces the concept of the New Statistics. Here, the focus shifts from reporting p-values to estimation of effect sizes and confidence intervals (CIs) as a way to better explain what a difference between groups may mean. To help facilitate a New Statistics approach, Ho, et al (2019) have developed a computer package, DABEST, for the creation of estimation graphics. These are data-rich plots which display effect sizes and CIs alongside graphical distribution of all data points from samples. In this presentation, following an overview of the issues above, I will introduce an online application for quantitative data analysis using DABEST. The application, built by the presenter, generates estimation plots and other essential statistical data to help researchers understand results from their research through a New Statistics framework, as well as providing output for use in presentations or publications.