AI Summary
[DOCUMENT_TYPE: user_assignment]
**What This Document Is**
This document outlines the requirements for the first project in STAT 6800, a SAS Programming course at Western Michigan University. It details an exploratory data analysis assignment designed to build foundational skills in SAS, focusing on data manipulation and descriptive statistics. The project requires students to select a dataset from a provided archive and perform analysis using SAS procedures. It’s a practical application of concepts learned in the course, moving beyond theoretical understanding to hands-on implementation.
**Why This Document Matters**
This project description is crucial for any student enrolled in STAT 6800. It serves as the definitive guide for completing the first major assessment. Students will benefit from carefully reviewing this document *before* beginning their work to ensure they understand the expectations regarding data selection, analysis techniques, report formatting, and collaboration guidelines. It’s particularly valuable for clarifying the scope of the project – emphasizing exploratory analysis rather than advanced statistical inference – and understanding the required deliverables.
**Common Limitations or Challenges**
This document provides a framework for the project but does *not* offer step-by-step instructions on *how* to perform the analysis. It lists available SAS procedures, but doesn’t demonstrate their application. Students will need to leverage their understanding of SAS syntax, utilize online documentation, and apply their problem-solving skills to successfully complete the assignment. It also doesn’t include the datasets themselves; those must be obtained separately from the specified archive.
**What This Document Provides**
* A list of approved datasets for the project, sourced from the Journal of Statistical Education Data Archive.
* Guidelines regarding team collaboration, including maximum team size and submission requirements.
* Detailed specifications for the project report, including formatting, length, and content expectations (cover page, table of contents, sections, appendices, summary).
* A list of recommended SAS tools and procedures for completing the exploratory data analysis (DATA step, PROC PRINT, PROC MEANS, PROC UNIVARIATE, etc.).
* Clear expectations regarding the inclusion of tables and graphs within the main report versus the appendices.