Juan Claramunt
Specialist scientific information, Methodology and Statistics unit, Institute of Psychology, Leiden University.
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Bachelor in Mathematics at Universidad de Cantabria, Utrecht University & Brown University.
Master in Methodology and Statistics for the Behavioural, Biomedical, and Social Sciences, & European Master in Official Statistics (Utrecht University).
Scientific information specialist at Leiden University since 2018. Research includes regression and classification trees, multiple imputation, or reproducibility in simulation studies. Coordinator of R seminars for five bachelor Statistics courses.
StatLearning: A shiny app for practicing statistical hypothesis testing
With this poster, we want to introduce StatLearning, our shiny app for practicing diverse statistical tests.
This app is a step forward in digital exercising. While many digital exercises only provide data and questions, StatLearning provides an individualized learning path. To do so, we analyzed the different types of students and their preferred learning styles (reading, watching, listening, etc.). Besides, apart from the data and questions, we provide the users with statistical definitions and help windows. These windows include written explanations and videos.
Moreover, we consider the diverse student's abilities, allowing students to skip steps if their statistical abilities are advanced while providing extra help for students with lower skills. This way, we aim for students with low abilities to reach advanced skills by practicing.
We aim to introduce StatLearning to other R users at the conference who might find it useful for their courses. Furthermore, we would like to receive feedback to improve our app. We have used this app for three years and keep improving it yearly. Therefore, any new suggestions are welcomed.
From SPSS to R in Social Sciences
In this session, we will discuss the transition from SPSS to R that we made at the Methodology and Statistics unit of the Institute of Psychology of Leiden University.
With this talk, we want to inspire and help other users to introduce R in their Social Sciences bachelors replacing other common software such as SPSS, as well as making connections with other R users willing to improve Data Science/Statistics education in Social Sciences.
We will introduce the main reasons for the change: alignment research-education, didactical purposes, incentivize good research practices (open science, reproducibility), and better career perspectives.
Afterwards, a description of the implementation of R in our bachelor program will be outlined. Here, we aim to provide tips on how to transition from SPSS to R in a social sciences environment, including the experience of other R users working on related education.
We finalize with a summary of the quantitative and qualitative results we have obtained during the first R year.
We anticipate the transition to R to greatly impact our students' future research practices, helping to solve issues such as the reproducibility crisis.
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