Shiny Apps Gallery

This site contains Shiny apps produced in the QHELP project. For educational purposes, the source code is shown with the apps.

You may also want to look at the Shiny apps produced in the predecessor project, TquanT.

Linear Regression:A learnr tutorial.

LexOPS finds characteristics of words from large corpora to be used in lexical studies.

Validating BLIM-simulated Data: This app does a series of BLIM simulations and shows the dependence of the Discrepancy Index from the noise. The app was inspired by a student app from the 2019 seminar.

Conditional Testing

Properties of Relations: This app allows you to define an arbitrary binary relation on a set of five items and shows you whether certain properties are fulfilled.

Modelling PISA Data by Clusters: An illustration of statistical learning and visualisation techniques using real-world data (PISA).

Distributions: An illustration of the effect of violations of assumptions for the F distribution.

QQplot: This Shiny app is meant to let you play around with a few different distributions (Normal, Skew Normal, Cauchy, Skew Cauchy), and check what the effect of different variables (scale, location and shape) on their qq-plot is.

QHELP is co-funded by the Erasmus+ Programme of the European Commission.

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Linear Regression:A learnr tutorial.	LexOPS finds characteristics of words from large corpora to be used in lexical studies.	Validating BLIM-simulated Data: This app does a series of BLIM simulations and shows the dependence of the Discrepancy Index from the noise. The app was inspired by a student app from the 2019 seminar.
Conditional Testing	Properties of Relations: This app allows you to define an arbitrary binary relation on a set of five items and shows you whether certain properties are fulfilled.	Modelling PISA Data by Clusters: An illustration of statistical learning and visualisation techniques using real-world data (PISA).
Distributions: An illustration of the effect of violations of assumptions for the F distribution.	QQplot: This Shiny app is meant to let you play around with a few different distributions (Normal, Skew Normal, Cauchy, Skew Cauchy), and check what the effect of different variables (scale, location and shape) on their qq-plot is.