Defining the 95% of data which are around the mean value

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Giorgos Papakonstantinou 2013-7-31

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For a given set of data, how can I define which of those correspond to the 95% of the data which are around the mean value?

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Answer 1

Jan 2013-8-1

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编辑：Jan 2013-8-1

在 MATLAB Online 中打开

x = rand(1, 1000) - 0.5;
m = mean(x);
dist = abs(x - m);
[sortDist, sortIndex] = sort(dist);
index_95perc = sortIndex(1:floor(0.95 * numel(x)));
x_95percent = x(index_95perc);

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Giorgos Papakonstantinou 2013-8-1

在 MATLAB Online 中打开

Thank you Jan. It was easier than I expected. Before your answer I was doing the folllowing:

vals=abs(slope);
[CdfY,CdfX] = ecdf(vals,'Function','cdf');  % compute empirical function
cr=CdfY<0.95;

where vals is my dataset.

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Answer 2

Image Analyst 2013-7-31

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I'd sort the data using sort(). Then use cumsum() to get the cdf. Normalize the CDF then go from the 2.5% element to the 97.5% element using find() to find the elements (values) where the data starts and stops. It's pretty easy, but let me know if you can't figure it out.

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Answer 3

Giorgos Papakonstantinou 2013-7-31

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Thank you for your answer Image Analyst. The data contain also negative values. I am not sure but I think that poses a problem when I normalize the data after the cumsum.

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Tom Lane 2013-8-1

It sounds like Image Analyst is talking about the cumsum of a vector that assigns probability 1/N to each of N points. However, you could take the 0.025*N and 0.975*N values from the sorted vector directly, converting the index to an integer as you see fit.

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