Fit a histogram and normal distribution to data

I have the following variable:

The numbers on the left column represent the bin edges and the numbers on the right column represent the percentage frequency of the bin. For example:

(>1400 = 0%) and (between 1000 and 1400 = 1.1961%) and (between 710 and 1000 = 2.26725%) and so on.

I would like to construct a histogram and a probability density function (I think a gaussian curve fits well).

The problem is that I do not know the exact code for this and that the bins are not all the same size.

[Mathieu Montoya]

did you try histfit ?

Answer 1

[Niels8]

Did anyone find the question to this?

I am having the same problem

Answer 2

[Image Analyst]

Use fitdist(). The example in the help is:

%%Fit a Normal Distribution to Data  

% Copyright 2015 The MathWorks, Inc.

Load the sample data. Create a vector containing the patients' weight data.

load hospital
x = hospital.Weight;

Create a normal distribution object by fitting it to the data.

pd = fitdist(x,'Normal')

Plot the pdf of the distribution.

x_values = 50:1:250;
y = pdf(pd,x_values);
plot(x_values,y,'LineWidth',2)

[Jurgen Casha]

the value of x only accepts the raw data. The problem is that i only know ranges of data. For example in this case between 0 and 75 there is 0.0194%.

[Image Analyst]

You can use the count values of your histogram bins for x. The "x_values" would be the values of the histogram bin centers.