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I've stopped using box plots (2021)

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Re: I've stopped using box plots (2021)

#121

Post by oefrha »

rzmmm wrote: post #67
ozyschmozy wrote: post #36

Earlier quoted context omitted.

> There are very real use cases for box plots, The author argues otherwise, can you give an example of a use case where box plots would be preferable to the alternatives the author suggests?

Often people are interested in exact quantitative statistics like IQR, median, top/bottom deciles which are commonly represented in box plots. The alternatives are visually simpler but they contain less quantitative information.

The alternative plots in TFA after

> Design concepts such as the ones below make more ‘visual sense’ than box plots:

present the exact same info in much less visually confusing ways, through the use of brightness (weight) and area. Just better box plots.

And of course you can always draw some lines for the quartiles on any kind of plot with a linear scale for the value.

Re: I've stopped using box plots (2021)

#122

Post by cb321 »

People have conflicting goals. On the one hand they long to compress many numbers into one or a few summary statistics. On the other hand, the moment such lusted after summaries mislead in some way they regret the data compression. What's really going on is that people want a simplicity (often in the form of definite conclusions) which may just not exist. This is really a common malaise of the human condition.

Similarly, the distribution represented by a box plot itself is often the distribution of "just one sample". When viewed as such, a distro has its own uncertainty[1] and that uncertainty is not represented in a violin plot, for example. As with every "right tool for the job" debate, people will vary based on experience with the tools, including how to simplify/explain them to others.

[1] https://github.com/c-blake/bu/blob/main/doc/edplot.md

Re: I've stopped using box plots (2021)

#123

Post by munch117 »

blueflow wrote: post #103
munch117 wrote: post #102

Earlier quoted context omitted.

Count data points in each quartile. You can do that for any sortable data, independent of distribution.

If you do that in your paper, you better write next to the graph that you did that.

Perhaps I expressed myself poorly, and left room for misunderstanding, because I cannot possible imagine that we have any real disagreement on how to compute quartiles.

Any set of numbers I give you, you can compute quartiles for it. There is no algorithm for doing that that breaks down if the numbers don't follow a normal distribution.

Re: I've stopped using box plots (2021)

#124

Post by blueflow »

thaumasiotes wrote: post #113
blueflow wrote: post #103

Earlier quoted context omitted.

If you do that in your paper, you better write next to the graph that you did that.

Arguing that nobody who might be professionally expected to look at a box plot can be reasonably expected to understand how box plots are defined doesn't make a compelling case that using them is a good idea.

If the method how the plot boxes are calculated is not clear (this thread references at least two different methods), you'll need to explicitly write it down which methods you did use.

Re: I've stopped using box plots (2021)

#125

Post by riedel »

Actually you may nicely integrate box, violin, bee/scatter plots [0]. For simple visual ANOVA testing box plots are great. On the other hand violin plots are great to quickly check distribution assumptions for testing and together with scatter plots give you a good impression of the sample.

[0] https://davidbaranger.com/2018/03/05/showing-your-data-scatt...

Re: I've stopped using box plots (2021)

#126

Post by commathingy »

thaumasiotes wrote: post #105
conformist wrote: post #99

Earlier quoted context omitted.

In the mathematical sense this is clearly not true - it’s easy to come up with a smooth single mode distribution that doesn’t look like a bell.

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

Re: I've stopped using box plots (2021)

#127

Post by sloowm »

These335 wrote: post #57

Sure there are alternatives and I agree with the author's criticisms overall. But boxplots are a staple in statistics, and if your audience can reasonably be assumed to have some level of statistical training then boxplots are perfectly reasonable in my opinion.

Are you sure that well trained audiences are able to accurately asses box plots. For instance, most drivers think they are better than average drivers.

It being a staple in statistics is also not a good argument. The information conveyed through box plots is used in lots of fields with different education backgrounds. If a visualization, which in itself is a human simplification of data, is hard to understand, it will be misunderstood by some. This means these people will not be able to advance their field of research as well as with better visualization methodologies.

Re: I've stopped using box plots (2021)

#128

Post by blueflow »

munch117 wrote: post #123
blueflow wrote: post #103

Earlier quoted context omitted.

If you do that in your paper, you better write next to the graph that you did that.

Perhaps I expressed myself poorly, and left room for misunderstanding, because I cannot possible imagine that we have any real disagreement on how to compute quartiles. Any set of numbers I give you, you can compute quartiles for it. There is no algorithm for doing that that breaks down if the numbers don't follow a normal distribution.

Look at this SVG from wikipedia: https://upload.wikimedia.org/wikipedia/commons/1/1a/Boxplot_...

When you calculate the box plot using normal distribution parameters, the outliers are outside the outer bracket.

If you split the dataset into 4 equal parts, the bracket will be larger because the outliers are still inside it.

The methodologies are not equal.

This thread is the first time i heard people do the "split dataset into 4 quarters" and using that for box plots.

Re: I've stopped using box plots (2021)

#129

Post by sloowm »

SillyUsername wrote: post #53
scrollaway wrote: post #49

Earlier quoted context omitted.

Yeah I'm shocked at the awful quality of comments here. This is a clear and straightforward article laying out the issues with box plots and appropriate alternatives, from a professional who works in the field and spends his life explaining these. And still half the comments are like "But I know better!"... yeah, I'd wager most here don't.

I'm qualified in maths related computing and statistics to exam invigilator level, if that helps offset your bias.

That background would make you explicitly unqualified to asses the quality of box plots as a visualization method. Box plots are used throughout various fields of research that are far less mathematical in nature.

Re: I've stopped using box plots (2021)

#130

Post by iainmerrick »

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?

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