# Histogram normalisation: a question about terminology

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Sim on 14 Jul 2023
Commented: Sim on 1 Aug 2023
Let's consider the histogram and histcounts functions, as in these two cases:
num_bins = 30; % <-- note: I specify the "number of bins" and not the "bin width", which can be different from 1
% Case 1
histcounts(X,num_bins,'Normalization','probability');
histogram(X,'NumBins',num_bins,'Normalization','probability');
% Case 2
histcounts(X,num_bins,'Normalization','pdf');
histogram(X,'NumBins',num_bins,'Normalization','pdf');
Do I understand correctly that
1. For Case 1, I get the "Relative Frequency Histogram" or an "empirical estimate of the Probability Mass Function"?
2. For Case 2, - where I divide by the bin widths as well -, I get the an "empirical estimate of the Probability Density Function"?
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Sim on 1 Aug 2023

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### Answers (1)

Satwik Samayamantry on 14 Jul 2023
Hi Sim,
Yeah you got it right. Your understanding for both cases is correct.
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Steven Lord on 1 Aug 2023
See the description of the Normalization name-value argument on either of the histogram or histcounts documentation pages. It describes exactly what the Values property of the histogram or the first output of the histcounts function represent.
Sim on 1 Aug 2023
thanks @Steven Lord :-)

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