Normalizing histograms and Finding best fit distribution

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To normalize histograms of packet arrivals, express the number of occurrences as a percentage of the total, ensuring they sum to 100%. This process transforms the data into probability mass functions. For finding the best fit distribution, the lognormal distribution is recommended as a starting point. Analyzing the fit can involve statistical tests or visual comparisons with the normalized data. Proper normalization and distribution fitting are essential for accurate data interpretation in network traffic analysis.
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I have plotted packets arriving in one second at a router. I then made histograms of the number of occurences of same number of packets in one second time window. My question is that I want to normalize these histograms. How can I do this to get probability mass functions. And then how do I check which distributions give the best fit for these histograms.
 

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To normalize, you should express the number of packets as percent of the total, so in the end they add up to 100%.

I'd start with the lognormal distribution.
 
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