Gourdon-Kanhukamwe, Amélie (2019) It’s time to break-up with SPSS! Moving to open stats software without pain. In: 10th Annual Faculty Conference: Contemporary Issues in Business and Social Sciences in a period of uncertainty; 03 - 04 Jun 2019, Kingston upon Thames, U.K.. (Unpublished)

Abstract

Have you ever thought SPSS was ‘so last century’? Have you ever wished using SPSS with point and click was friendlier? Are you tempted to explore Bayesian statistics but are not ready to learn R? Do you think SPSS cost too much and are you concerned that your analyses can only be read if you have access to an SPSS software? JASP© (Jeffreys’s Amazing Statistics Program) is a software originally developed by a team at University of Amsterdam, as an open-source project. It is free to use and supported by funding that will allow the team to develop the software in the long term. JASP© is further distinct from SPSS in two ways. The user interface was developed so that it is more intuitive and user-friendly. For example, JASP© computes your analysis dynamically as you choose your options; therefore, if one makes a mistake after clicking OK on their analysis, they can edit that analysis directly, instead of running it again. Secondly, JASP© not only offers the main frequentist tests SPSS allows one to do, but for most of them, it also offers users its Bayesian inference framework alternative. Alternatively, jamovi© is another open-source project, with the same dynamic features as JASP©. Unlike JASP©, jamovi© does not allow to perform Bayesian inference tests with point and click, but it allows to see the R code required by your analysis, instead of hiding it behind the scenes. It is therefore a useful tool for any researcher that would like to start learning R coding: the point-and-click software provides scaffolding, leading to a gentler learning curve. In this talk, I intend to demonstrate how researchers can use these open software options to move away from SPSS. I will demonstrate common frequentist hypothesis tests in both software, and Bayesian ones in JASP©, to articulate how and when each software is most appropriate. I will provide these demonstrations using screen-casting, so that attendees can refer back to them when they later try and explore the two software options. Seminar attendees are encouraged to download JASP© as well as jamovi© before the seminar, and to bring their laptop in the seminar so they can practice during the presentation, if they wish to.

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