SAS

This course introduces students to basic knowledge in programming, data management, and exploratory data analysis using SAS software. Students are provided the opportunity to learn a comprehensive set of SAS data-related techniques through lessons, demonstrations, and homework assignments. The material covered in Stat 480, in conjunction with the material covered in the sequel course STAT 481, is designed to prepare students for taking the SAS Version 9 Base Programming Certification Exam.

Stat 481 (Intermediate SAS) builds on the skills and tools learned in Stat 480 (Introduction to SAS) to extend students' SAS programming skills to an intermediate-level. Students are provided the opportunity to learn a comprehensive set of SAS data-related techniques through lessons, demonstrations, and homework assignments. The material covered in Stat 481, in conjunction with the material covered in the prerequisite course Stat 480, is designed to prepare students for taking the SAS Version 9 Base Programming Certification Exam.

The goals of the course are:

  1. to prepare students (in conjunction with Stat 480) for taking the SAS Version 9 Base Programming Certification Exam
  2. to introduce you to the wide variety of programming and data management tools available in the SAS software application
  3. to further increase your confidence in understanding and programming in SAS
  4. to extend your understanding of how the SAS application can be used effectively to manage and manipulate data
  5. to extend your knowledge of good programming practices

This course is a combination of a sequence of three one-credit classes on SAS programming (Stat 480, 481, and 482).  The class is organized into three five-week segments.

This is a graduate level course in analysis of variance (ANOVA), including randomization and blocking, single and multiple factor designs, crossed and nested factors, quantitative and qualitative factors, random and fixed effects, split plot and repeated measures designs, crossover designs and analysis of covariance (ANCOVA). This course is cohort-based, which means that there is an established start and end date, and that you will interact with other students throughout the course.

Students completing this course should be able to:

  • Select appropriate methods of multivariate data analysis, given multivariate data and study objectives;
  • Write SAS and/or Minitab programs to carry out multivariate data analyses;
  • Interpret results of multivariate data analyses.