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sorry if this is a dupe, however I am not sure what to search for. I am a software programmer and not a statistical guy by any measure.

I am attempting to plot some data collected over time. I take sample data every second but want to display the data at a higher level since I don't want to be plotting thousands of points. I still need to show that there were large variances. I don't know how to calculate this, or if there is a correct way of doing so.

Take for example, this sample set. 98, 100, 110, 1500, 120 the mean is 401.8 but I'd like to acknowledge that the 1500 occurred, and if the inverse occurred I'd like to show that also.

Is there a way of calculating the mean taking into account such variance?

Is that an acceptable way to show such data or is the mean acceptable?

I don't necessarily need a solution, but perhaps some direction.

Thanks in advance.

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I think you need to look up standard deviation.

Perhaps look up the R programming language too.

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This would better be a comment, but since it has been upvoted, I will leave it as an answer. – robjohn Nov 14 '12 at 9:58

The box-whisker plot is a fairly standard solution to visualize this kind of information. It displays the median, the interquartile range, as well as the minimum and maximum of the data. Thus, it gives a good idea of the spread of the middle of the data as well as the extremes. (The median is more informative than the mean here, because it is resistant to outliers.)

Here's what it looks like for your data. Given the enormous range, I've drawn it on a logarithmic scale.

enter image description here

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