# Model for diurnal nature of data [closed]

I have a timeseries dataset of a quantity measured over the period of a week. I want to verify if the data is varying in a diurnal fashion with the help of some mathematical measure. Does any such measure exist?

## closed as off-topic by David Richerby, vonbrand, András Salamon, Luke Mathieson, JuhoFeb 2 '14 at 11:28

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• "This question does not appear to be about computer science, within the scope defined in the help center." – David Richerby, vonbrand, András Salamon, Luke Mathieson, Juho
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• That depends no the process. If the data are supposed to depend mostly on time of day, Markov chains may be suitable. It's hard to say without background. – Raphael Jan 22 '14 at 9:23
• This doesn't seem to be a computer science question. The stats Stack Exchange would be much more appropriate. – David Richerby Jan 31 '14 at 11:19

If you want to find periodic behaviors of your data, you should use the Fourier transform, which decomposes your data into a linear combination of cyclic waveforms. If you have a guess on the actual period, as in your case, you can try something simpler. For each hour during the day, compute the mean $\mu$ and variance $\sigma^2$ of your data, and plot the intervals $[\mu-\sigma,\mu+\sigma]$ for each hour. That should give you an idea regarding your hunch. (More generally, you can try a sophisticated method like ANOVA.)