The histogram distribution can be constructed with Crystal Ball's Custom distribution

Histogram equations=

The Histogram distribution takes three data arrays: the=
first column lists the minimum of each range; the second column lists the =
maximum; and the third column lists the frequencies (or relative frequencie=
s) for the bands between the minimum and maximum. In Crystal Ball, one has =
to use the Crystal Ball's Custom Distributio=
n to construct a Histogram distribution.

The figure below plots an example.

Histogram dis=
tribution using data: ({2,3,4,5,6,7,8},{3,4,5,6,7,8,9},{1,2,4,6,3,2,1}),

constructed with Crystal =
Ball's Custom Distribution

#### Uses

The distribution is useful in a non=E2=80=93parametric =
technique for replicating the distribution s=
hape of a large set of data. The technique is simply to collate the dat=
a into i bands that each have a minimum and maximum you specif=
y, calculate the number of data values that fall into each band, and then u=
se this information to define the distribution. It has the disadvantage of =
'squaring off' into the histogram shape, but with a lot of data and small b=
ands the technique is a transparent and practical way of fitting a distribu=
tion to data.

Crystal Ball automatically normalizes the distribution =
to have an area of one.

The histogram distribution is quite closely related con=
ceptually to the General distribution.

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