Histogram with a distribution fit (2024)

Generate a sample of size 100 from a normal distribution with mean 10 and variance 1.

rng default; % For reproducibilityr = normrnd(10,1,100,1);

Construct a histogram with a normal distribution fit.

histfit(r)

histfit uses fitdist to fit a distribution to data. Use fitdist to obtain parameters used in fitting.

pd = fitdist(r,'Normal')

pd = NormalDistribution Normal distribution mu = 10.1231 [9.89244, 10.3537] sigma = 1.1624 [1.02059, 1.35033]

The intervals next to the parameter estimates are the 95% confidence intervals for the distribution parameters.

Generate a sample of size 100 from a normal distribution with mean 10 and variance 1.

rng default; % For reproducibilityr = normrnd(10,1,100,1);

Construct a histogram using six bins with a normal distribution fit.

histfit(r,6)

Generate a sample of size 100 from a beta distribution with parameters (3,10).

rng default; % For reproducibilityb = betarnd(3,10,100,1);

Construct a histogram using 10 bins with a beta distribution fit.

histfit(b,10,'beta')

Generate a sample of size 100 from a beta distribution with parameters (3,10).

rng default; % For reproducibilityb = betarnd(3,10,[100,1]);

Construct a histogram using 10 bins with a smoothing function fit.

histfit(b,10,'kernel')

Generate a sample of size 100 from a normal distribution with mean 3 and variance 1.

rng('default') % For reproducibilityr = normrnd(3,1,100,1);

Create a figure with two subplots and return the Axes objects as ax1 and ax2. Create a histogram with a normal distribution fit in each set of axes by referring to the corresponding Axes object. In the left subplot, plot a histogram with 10 bins. In the right subplot, plot a histogram with 5 bins. Add a title to each plot by passing the corresponding Axes object to the title function.

ax1 = subplot(1,2,1); % Left subplothistfit(ax1,r,10,'normal')title(ax1,'Left Subplot')ax2 = subplot(1,2,2); % Right subplothistfit(ax2,r,5,'normal')title(ax2,'Right Subplot')

Generate a sample of size 100 from a normal distribution with mean 10 and variance 1.

rng default % for reproducibilityr = normrnd(10,1,100,1);

Construct a histogram with a normal distribution fit.

h = histfit(r,10,'normal')

h = 2x1 graphics array: Bar Line

Change the bar colors of the histogram.

h(1).FaceColor = [.8 .8 1];

Change the color of the density curve.

h(2).Color = [.2 .2 .2];

h — Handles for the plot
plot handle

Handles for the plot, returned as a vector, where h(1) is the handle to the histogram, and h(2) is the handle to the density curve. histfit normalizes the density to match the total area under the curve with that of the histogram.