Subject: STA 201
Title: SAS Programming for Statistical Analysis
Units: 3.0
School: College of Letters and Science LS
Department: Statistics STA
Effective Term: 2013 Fall Quarter
Learning Activities
- Lecture - 2.0 hours
- Discussion/Laboratory - 1.0 hours
Description
Introductory SAS language, data management, statistical applications, methods. Includes basics, graphics, summary statistics, data sets, variables and functions, linear models, repetitive code, simple macros, GLIM and GAM, formatting output, correspondence analysis, bootstrap. Prepare SAS base programmer certification exam.
Prerequisites
Introductory, upper division statistics course; some knowledge of vectors and matrices; STA 106 or STA 108 or the equivalent suggested.
Expanded Course Description
Summary of Course Content:
Detailed SAS content: 1. Data input using SAS (formatted and list input, data set importing), modification and combination of SAS data sets (5 lectures) 2. Summarization of data (1 lecture) 3. Use of SAS statistical procedures (1 lecture) 4. By processing (1 lecture) 5. ODS features for managing SAS output and results (1 lecture) 6. Arrays and Do loop processing (1 lecture) 7. Introduction to macro processing (1 lecture) 8. Customized formatting (1 lecture) 9. SAS graphical features (1 lecture) Statistical content: 1. Linear and mixed linear model analysis (1 lecture) 2. Validation of model assumptions (2 lectures) 3. Generalized linear and generalized additive models (1 lecture) 4. Bootstrap and cross-validation (2 lectures)
Illustrative Reading:
The Little SAS Book, by Delwiche and Slaughter
Potential Course Overlap:
There is a minor overlap with STA 206-207 which will focus on statistical concept and methods and some of the data analysis will be done by SAS. This course emphasizes data management and introduces students to the vast available statistical procedures in SAS, along with preparing the students for basic SAS certification exam.