131–140 of 258 posts
The author just has a bad intuition. On the first picture he says "this looks like a small quantity". No, you can't say that. All you can say is that half the data points are in the shades part. You don't know where the rest are.
Earlier quoted context omitted.
While true, that's not an additional problem compared to box plots which effectively just set the bandwidth to maximum. So IMO they are strictly better.
I find violin plots suggest far smoother results than actually exist so you need to be careful with the amount of data.
Earlier quoted context omitted.
You're right. I guess that's not the author's mistake then. His mistake is assuming "the whisker is small, therefore it has a small number of datapoints".
That's not his mistake. He knows this, but repeatedly failed to convey this to others. That's like the entire point of the post: they're hard to teach to others (they're unintuitive) and there are better (more intuitive) alternatives. I dunno if I agree, but it's ironic that this thread started with a poster complaining about the author's bad intuition, while apparently managing to not have a good grasp of box plots…
Also, that IS his mistake, it's literally the first thing in the post. And this stuff isn't hard or hard to teach _at all_ has long as you're at least 5.
https://en.wikipedia.org/wiki/Sina_plot
https://cran.r-project.org/web/packages/sinaplot/vignettes/S...
Adding on a representation of mean in a different style (like a black bar) can be helpful. So can a boxplot-style indication of variance, in some cases.
Lots of people defending box plots here -- a lot more than I expected! What I don't see is anyone saying "box plots are useful because they're the best kind of chart for [specific use case]". I can't off-hand think of any situation where I'd rather see a box plot than a strip plot or violin plot. When and why would you want to summarise the data so coarsely and visualize it so un-intuitively?
Box plots are useful because they're the best kind of chart for when I have multiple populations and I want to quickly glance whether it's reasonable to assume that the populations have the same median, or not (you do that comparing not just the medians of the populations but also the shaded areas)
Earlier quoted context omitted.
That's not his mistake. He knows this, but repeatedly failed to convey this to others. That's like the entire point of the post: they're hard to teach to others (they're unintuitive) and there are better (more intuitive) alternatives. I dunno if I agree, but it's ironic that this thread started with a poster complaining about the author's bad intuition, while apparently managing to not have a good grasp of box plots…
What are you talking about? I have a perfect grasp of these things. As I said, half is in the shape area. You must've missed that. Also, that IS his mistake, it's literally the first thing in the post. And this stuff isn't hard or hard to teach _at all_ has long as you're at least 5.
> You don't know where the rest are.
This is wrong, period. And the fact it's wrong is pretty much the entire point of the article.
Are bdjsiqoocwk and lkdfjlkdfjlg the same poster?
Please don't pick a needless fight.
Earlier quoted context omitted.
Is it? How? You could include a lot of little bells far from the single mode, but that's reading a little too much into the literal meaning of "single mode" - a "bimodal" distribution isn't one where the two most common values are both modes. It's one where there are two distinct local maxima. The tails to the left and right must asymptotically approach zero (or you don't have a smooth distribution, because you have…
The exponential distribution (modal value 0) is not bell shaped. If you don't like it's range of non-negative, then take some smooth mollification
So the diagram should not be used because of an education problem with some audiences? Isn't that a bit like banning cars because some people can't drive? Some diagrams are simply not for mass consumption and this is one, particularly because it is designed to illustrate an interpretation of ranges instead of the direct/linear representation of the raw data. Of course I'd illustrate this fact as a Venn diagram compar…
A problem like this one that he mentions, "People associate longer shapes with greater quantity", is not something you can fix by teaching. Even if you know intellectually that the association is, in this case, wrong, you can't free yourself from the association. It's hardwired into the brain.
People who work with this sort of diagram a lot will eventually build up context-specific associations that work better, overriding that instinct, to the point where it feels seamless. But even if it feels seamless and easy, the dissonance is still there, and may lower your comprehension speed and slightly impair your judgment.
As a statistics expert, you are never going to notice that, because your baseline comprehension speed and judgment on the subject is so good, that this very minor impairment is lost in the noise. So you may not be a good judge of the usability qualities of the diagram type.