Computing and graphing probability values of pearson distributions: a SAS/IML macro.

Area of Science:

• Statistics
• Computational Statistics

Background:

• Empirical data can be approximated using Pearson distributions based on the first four moments.
• Existing methods for calculating Pearson distribution percentage points are cumbersome for statistical analysis.

Purpose of the Study:

• To develop a SAS/IML macro program for identifying Pearson distribution types and computing probability values.
• To provide a tool that simplifies statistical analysis for data with unknown distributions.

Main Methods:

• Developed a SAS/IML macro program.
• The program identifies Pearson distribution types from datasets or moment values.
• Computes and graphs probability values for any given percentage points.

Main Results:

• The SAS macro program accurately approximates Pearson distributions.
• The tool efficiently identifies the correct Pearson distribution type.
• It computes probability values for any specified percentage points.

Conclusions:

• The SAS macro program facilitates accurate statistical analysis of data with unknown distributions.
• Researchers can efficiently conduct analyses using this new computational tool.