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I am trying to visualize an appropriate plot for the observations in this table of means and standard deviations of recall scores:

\begin{array} {c|c c|c c|} & \text{Control} & & \text{Experimental} & \\ & \text{Mean} & \text{SD} &\text{Mean} &\text{SD} \\ \hline \text{Recall} & 37 & 8 & 21 & 6 \\ \hline \end{array}

What is is the best way to do that? Is bar chart a good way to do it? How can I illustrate the standard deviation in that case?

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    $\begingroup$ If you don't have more data, I would not create a graph. It would be a waste of space. $\endgroup$
    – Roland
    Commented Oct 19, 2015 at 13:33
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    $\begingroup$ If you don't have more than this, a full analysis is difficult, as these means and SDs are compatible with many different distributions. $\endgroup$
    – Nick Cox
    Commented Oct 19, 2015 at 17:27

3 Answers 3

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Standard deviation on bar graphs can be illustrated by including error bars in them.

The visualization(source) below is an example of such visualization:

enter image description here


From a discussion in the comments below, having only the error whiskers instead of the error bars setup seems a better way to visualize such data. So, the graph can look somewhat like this:

enter image description here

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    $\begingroup$ The principle is clearly along the right lines, but I'd suggest refinements to your graph. If bins are for touching intervals, then the bars should touch too and indicating bin boundaries alone is sufficient. Regardless of that, the cross-hatching is, in my view, just a distraction here. BTW, how would you denote error for a zero observed count? $\endgroup$
    – Nick Cox
    Commented Oct 19, 2015 at 12:29
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    $\begingroup$ At least this example has the error bars on both sides, the worst "dynamite plots" don't even have those, see here for one example. $\endgroup$
    – Andy W
    Commented Oct 19, 2015 at 12:32
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    $\begingroup$ No! I meant plotting error whiskers without plotting the bars. Bars are bad. $\endgroup$
    – amoeba
    Commented Oct 19, 2015 at 12:43
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    $\begingroup$ I think bars can be fine for small counts, as in this example, and for some other measured quantities also with natural origin and reference level zero, so long as they don't occlude error bars. But bars can be silly and distracting (rather than bad) when it's not an issue whether values are or aren't zero. $\endgroup$
    – Nick Cox
    Commented Oct 19, 2015 at 13:33
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    $\begingroup$ Another possibility is a Cleveland dot plot (pdf), which is essentially the same as your dot & whisker version, except they go horizontally. Error bars are less common on dot plots, but are certainly acceptable. $\endgroup$ Commented Oct 19, 2015 at 15:31
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I'd suggest a dot plot:

Although there is still some room for improvement (perhaps dimming the edges of the big rectangle surrounding the data), almost all of the ink is being used to display information.

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    $\begingroup$ How does this answer the OP's question? How do you use dotplot with means and standard deviations? $\endgroup$ Commented Oct 19, 2015 at 18:36
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    $\begingroup$ This Stack Overflow page discusses how to generate dotplots from means and SDs. $\endgroup$
    – EdM
    Commented Oct 19, 2015 at 18:46
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    $\begingroup$ @kjetilbhavlorsen: The mean is the dot, and the standard deviation (or optionally, standard error of the mean) is shown using the length of the lines adjacent to the dot. $\endgroup$
    – user92562
    Commented Oct 19, 2015 at 19:05
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    $\begingroup$ (+1) The term "dot plot" is rather overloaded, my first thought was that you were going to suggest drawing dots for each data point (which of course the OP can't do, not having the raw data). I suspect this is what @kjetil wondered too. Does this variety of "dot plot" have a more specific name which distinguishes it from the "dot for each data point" type of plot? $\endgroup$
    – Silverfish
    Commented Oct 19, 2015 at 20:27
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Perhaps the best way to visualise the kind of data that gives rise to those sorts of results is to simulate a data set of a few hundred or a few thousand data points where one variable (control) has mean 37 and standard deviation 8 while the other (experimental) has men 21 and standard deviation 6. The simulation is simple enough in a spreadsheet or your favourite stats package. You can then graph the two distribitions to get an impression of the extent that the two sets of recall scores vary.

simple Excel graph

With a simuated data-set you can also easily construct summary graphs like box-plots or histograms with error bars.

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