The HISTOGRAM statement produces histograms and optionally superimposes approximated parametric and probability that is nonparametric curves. You can’t make use of the BODY WEIGHT declaration utilizing the HISTOGRAM statement. You can make use of any true wide range of HISTOGRAM statements after a PROC UNIVARIATE declaration. The the different parts of the HISTOGRAM statement are follows.

would be the factors which is why histograms can be developed. In the event that you specify a VAR declaration, the factors additionally needs to be placed in the VAR statement. Otherwise, the factors may be any variables that are numeric the input information set. Then by default, a histogram is created for each numeric variable in the DATA= data set if you do not specify variables in a VAR statement or in the HISTOGRAM statement. By using a VAR statement nor specify any variables within the HISTOGRAM statement, then by standard, a histogram is established for every adjustable placed in the VAR statement.

For example, suppose a data set known as Steel contains precisely two numeric factors called measurements . The statements that are following two histograms, one for Length plus one for Width :

## Likewise, the statements that are following histograms for measurements :

The statements that are following a histogram for Length just:

add features into the histogram. Specify all options following the slash (/) within the HISTOGRAM statement. Choices is usually the immediate following:

main alternatives for installed distributions that are parametric kernel thickness quotes

secondary choices for fitted distributions that are parametric kernel thickness quotes

basic choices for images and production information sets

The NORMAL option displays a fitted normal curve on the histogram, the MIDPOINTS= option specifies midpoints for the histogram, and the CTEXT= option specifies the color of the text for example, in the following statements

Dining table 4.11 through Table 4.23 list the HISTOGRAM choices by function. For complete descriptions, begin to see the parts Dictionary of Alternatives and Dictionary of Common Options.

## Parametric Density Estimation Alternatives

Dining table 4.11 listings main choices that show parametric density quotes regarding the histogram. You are able to specify each main option when in a given HISTOGRAM statement, and every main choice can show numerous curves from the family members regarding the histogram.

## Dining Table 4.11 Primary Alternatives For Parametric Fitted Distributions

Fits distribution that is beta limit parameter , scale parameter , and form parameters and

fits exponential circulation with limit parameter and scale parameter

fits gamma distribution with limit parameter , scale parameter , and form parameter

Fits distribution that is lognormal threshold parameter , scale parameter , and form parameter

fits normal circulation with mean and deviation that is standard

fits Johnson circulation with limit parameter , scale parameter , and form parameters and

fits Johnson circulation with limit parameter , scale parameter , and form parameters and

fits Weibull circulation with limit parameter , scale parameter , and form parameter

Dining table 4.12 through Table 4.20 list additional choices that specify parameters for installed parametric distributions and that control the display of fitted curves. Specify these additional options in parentheses after the distribution option that is primary . As an example, you can easily fit a curve that is normal indicating the standard choice the following:

The curve is drawn by the COLOR= normal-option in red, while the MU= and SIGMA= normal-options specify the parameters and also for the bend. Observe that the test mean and sample standard deviation are acclimatized to calculate and , respectively, once the MU= and SIGMA= normal-options aren’t specified.

It is possible to specify listings of values for additional choices to display multiple fitted curve from the exact same distribution household on a histogram. Choice values are matched by list place. You are able to specify the worthiness EST in a listing of distribution parameter values to utilize an estimate regarding the parameter.

For instance, the code that is following two normal curves on a histogram:

The first curve is red, with and . The curve that is second blue, with corresponding to the sample mean and corresponding to the sample standard deviation.

Look at area Formulas for Fitted Continuous Distributions for step-by-step information regarding the grouped groups of parametric distributions that you could fit aided by the HISTOGRAM statement.