The present Shiny-App is an example of user-friendly method to directly elicit and formalize experts' knowledge about effect sizes when we are interested in the difference between the mean scores of two groups on a continuous variable. We used as an example average boys' and girls' height
Experimental data can broadly be divided in discrete or continuous data. Continuous data are obtaine...
This is a link to the Bad Visualisation Shiny App source code. A live version of the app is hosted...
Researchers in the field of psychology often face the situation that the statistical significance de...
Alternative displays of effect size statistics can enhance the understandability and impact of valid...
In this article we discuss our attempt to incorporate research-informed learning and teaching activi...
Although distributional inequality and concentration are important statistical concepts in many rese...
This is the accepted version of the following article: Gonzalez, J., Lopez, M., Cobo, E., Cortes, J....
Statistics education can be enhanced by technology. This thesis describes the theory and development...
This article introduces how to use the Shiny App in R to create interactive data visualization (from...
Statistical power is an important topic taught in most graduate-level and undergraduate-level mathem...
This short paper reviews the reasons why effect sizes are worthy of reporting and consideration when...
This Shiny App is designed to help users define their priors in a linear regression with two regress...
An interactive shiny app to enable users to create custom figures based on their differential expres...
This Shiny app calculates the probability of detecting disease at the given (within-population) prev...
Experimental data can broadly be divided in discrete or continuous data. Continuous data are obtaine...
Experimental data can broadly be divided in discrete or continuous data. Continuous data are obtaine...
This is a link to the Bad Visualisation Shiny App source code. A live version of the app is hosted...
Researchers in the field of psychology often face the situation that the statistical significance de...
Alternative displays of effect size statistics can enhance the understandability and impact of valid...
In this article we discuss our attempt to incorporate research-informed learning and teaching activi...
Although distributional inequality and concentration are important statistical concepts in many rese...
This is the accepted version of the following article: Gonzalez, J., Lopez, M., Cobo, E., Cortes, J....
Statistics education can be enhanced by technology. This thesis describes the theory and development...
This article introduces how to use the Shiny App in R to create interactive data visualization (from...
Statistical power is an important topic taught in most graduate-level and undergraduate-level mathem...
This short paper reviews the reasons why effect sizes are worthy of reporting and consideration when...
This Shiny App is designed to help users define their priors in a linear regression with two regress...
An interactive shiny app to enable users to create custom figures based on their differential expres...
This Shiny app calculates the probability of detecting disease at the given (within-population) prev...
Experimental data can broadly be divided in discrete or continuous data. Continuous data are obtaine...
Experimental data can broadly be divided in discrete or continuous data. Continuous data are obtaine...
This is a link to the Bad Visualisation Shiny App source code. A live version of the app is hosted...
Researchers in the field of psychology often face the situation that the statistical significance de...
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