## Fpower

An app on power calculation for the ANOVA F test.

## Generalizability of Fit

An illustration of the concept of generalizability of a fitted statistical model. In the first row a series of models have been fitted to observed data. In the second row, you see how the fitted models from the first row generalize to a new sample.

## Distributions

This app illustrates the effect of violations of assumptions for the F distribution.

## IRT Tutorial (Item Response Theory)

This learnr tutorial is based on a tutorial developed by students at the TquanT 2018 Seminar in Glasgow.

## Model Comparison Approach: Model 1

The Model Comparison App is focused on linear modeling inferential statistics and describe the computation of linear estimators based on the data (i.e., the model estimation), the test of the fit of the model to the data (i.e., interpreting the parameters estimates and respective error) and the generalization of the the results to the population…

## Model Comparison Approach: Model 2

The Model Comparison App is focused on linear modeling inferential statistics and describe the computation of linear estimators based on the data (i.e., the model estimation), the test of the fit of the model to the data (i.e., interpreting the parameters estimates and respective error) and the generalization of the the results to the population…

## Probability Distributions

This app allows a user to explore many different probability distributions in an interactive manner. The user can choose from several discrete and continuous distributions and observe how they react to interactively changing their parameters.The app is based on a student app from the TquanT Seminar 2018 in Glasgow.

## Selection Decisions in Diagnostic Applications

This app illustrates theoretical concepts that are relevant when a diagnostic test is applied in connection with a dichotomous (pass/fail) decision. The user is invited to explore the effects of several factors on the validity of the selection decision, and how these factors influence each other.

## Urn Problems

This app illustrates and visualizes four different discrete distributions via the urn model. It allows a user to change the properties of an urn and draw from it in order to get a feeling for the probabilistic mechanism represented by the corresponding theoretical distribution.

## Excess of Success

This app illustrates key concepts in Francis’s (2012) paper on replication in psychology: first, the excess of success, that is observing more successful replications than what would be expected within classical null hypothesis testing; second, a publication bias test that tests for too many successful replications.