App overview
In the app you can render lineups to investigate associations across groups. To use the app:
- Choose a data set or upload your own.
- Specify the response and explanatory variables.
- Generate a lineup of stacked bar charts or mosaic plots.
- Inspect the lineups and reveal the data plot.
After inspecting the lineup, you can focus on the observed data in the data plot tab.
Learning goals
This app is intended to introduce students to the logic behind hypothesis tests for
an association. After exploring the app, students should understand that identifying
the data plot indicates that either the data are systematically different from what
would be expected if no association exists, or that they were 'lucky' in their guess.
Further, students should understand that variability exists when there is no association,
which is why we need to rely on inferential procedures to help us understand whether we
observed signal or noise.
Example class usage
I recommend building a guided activity for your students.
- Introduce the data set and problem.
- Ask students to state their hypotheses in words (or notation).
- Ask students how they would display the sample data to review EDA.
- Have students generate a lineup. Quickly explain that one panel displays
the observed data while the other panels are decoy plots generated
under the assumption that no association exists between the variables.
Have students choose the plot that is most different and justify their
answer before revealing the answer.
- Ask students to discuss their decision in light of the 'answer' and
whether that supports one of the competing claims.
Additional resources
Below are additional resources to help you learn about visual inference and how it can be used in
the classroom:
Author
Adam Loy -
aloy.rbind.io
This work is licensed under a
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