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Programming with SAS/IML(R) Software

Course Details
Code: IMLP41
Tuition (USD): $2,400.00 • Classroom (3 days)
Course Details
GSA (USD): $2,176.32 • Classroom (3 days)
This course teaches you how to use the IML procedure via the programming language. You benefit from this course if you plan to use SAS/IML for manipulating matrices, simulating data, writing custom statistical analyses, or working with R. The programs in this course require SAS/IML 12.3 or later to run.

The self-study e-learning includes:

  • Annotatable course notes in PDF format.
  • Virtual lab time to practice.

Skills Gained

  • Create and manipulate matrices.
  • Move data between IML matrices and SAS data sets.
  • Simulate data.
  • Write, store, and retrieve IML modules.
  • Run SAS procedures from within IML.
  • Interface with R from within IML.

Who Can Benefit

  • SAS programmers, statisticians, econometricians, engineers, or others who want to use matrix algebra, simulate data, write custom statistical analyses, or work with R from IML

Prerequisites

  • Before attending this course, you should:
  • Have completed the SAS(R) Programming I: Essentials course or understand the material within.
  • Have completed the Statistics I: Introduction to ANOVA, Regression, and Logistic Regression course or understand the material within.
  • Possess an understanding of elementary matrix algebra or linear algebra concepts and operations, including matrix dimensions, matrix addition and multiplication, matrix inversion, and scalars.

Course Details

Fundamentals of IML

  • Creating and manipulating matrices.
  • Assignment statements and operators
  • accessing submatrices.

Modules, Logic, and Data

  • Transferring data between matrices and data sets.
  • Using IML modules.
  • Loops and conditional logic.

Program Development

  • Writing IML modules.
  • Storage and memory.
  • Efficiency and error handling.
  • Calling SAS procedures from IML.

Simulating Data

  • Random number generators.
  • Monte Carlo simulation.

Working with R

  • Setting up SAS and R.
  • Transferring data between SAS and R.
  • Running R analyses from IML.
  • Creating R graphics from IML.