R-ecology-lesson
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datacarpentry
add challenge about boxplot outlier plotting
I added a question to the challenges after the boxplot section that asks learners to reflect on the alpha parameter and its effects. It doesn't get clarified elsewhere that setting alpha to zero for the boxplot layer leads to the removal of the outlier points. When we taught the material, we noticed that the parameter often got removed during the exercises, which leads to double-plotting of the outliers, once in the boxplot and once in the jitter layer. I thought it could be helpful to make it part of the challenge to understand this behaviour and find a way of combining a jitter and a boxplot layer without duplicated outliers and without changing the transparency.
Thank you for the PR! I agree with your point -- I think when I was teaching this recently, I also explained the problem with duplicating outliers and how to remove the outliers in the box+jitter plot. This should definitely be adressed in the lesson.
(Another thing, although maybe not necessary to fix in this PR: the challenge does not have an answer and is complicated enough that it would benefit form having one, I think. This is related to #718)
Yes, definitely. I was unsure if I should just add a solution to the outlier issue or the whole block of challenges. If you want, I can give it a go and add answers for the whole block.
That would be fantastic! I already made a suggested solution in #718, I think, but wasn't able to test it properly.
(Note that the way answer blocks/chunks are marked in the RMarkdown is a bit weird. For one, they are sort of duplicated so that they show up in the code handout. Let me know if you need help with that.)
I'm helping the current lesson Maintainers process outstanding pull requests on this repository, in preparation for transition to the new lesson infrastructure.
Thank you for this contribution @haasek. With https://github.com/datacarpentry/R-ecology-lesson/pull/817, outlier.shape = NA has replaced alpha = 0 in the lesson text. There seems to be general agreement that this update makes the lesson clearer for learners! Thank you for contributing to this discussion.
