What This Document Is
This is a class exercise designed to reinforce practical skills in computing for statistics, specifically within a Statistical Computing (STAT 540) course at the University of South Carolina. It centers around the application of the SAS programming language and focuses on utilizing and understanding pre-built macros for statistical analysis. The exercise builds upon concepts introduced in the textbook “The Little SAS Book” by Delwiche and Slaughter. It’s a hands-on learning experience intended to solidify understanding through code implementation and data manipulation.
Why This Document Matters
This exercise is invaluable for students learning to apply statistical theory using a powerful software package. It’s particularly helpful for those who benefit from a step-by-step, practical approach to learning SAS. Students preparing for more advanced statistical computing coursework, or those needing to perform data analysis in fields like public health, economics, or research, will find this exercise beneficial. It’s best utilized *after* foundational SAS concepts have been introduced and a basic understanding of statistical sampling and regression is established.
Common Limitations or Challenges
This exercise does not provide a comprehensive introduction to the SAS language itself. It assumes a baseline familiarity with SAS syntax and data management. It also doesn’t cover the theoretical underpinnings of statistical sampling or regression analysis in detail – it focuses on *how* to implement these techniques in SAS, not *why* they work. The exercise relies on specific datasets and macro files, which are not included within this overview.
What This Document Provides
* Guidance on utilizing two specific SAS macros: ‘strata’ and ‘regall’.
* A practical application of calculating probabilities related to sampling techniques.
* An exploration of data manipulation techniques within SAS, including transposing data and creating new variables.
* A framework for performing simple linear regressions using a macro-driven approach.
* Opportunities to analyze the intermediate outputs generated by the macros to understand their functionality.
* A focus on efficient coding practices within SAS, including the appropriate use of DATA steps versus macro statements.
