

Course ID:  STAT 4355/6355. 3 hours. 
Course Title:  Advanced Statistical Programming 
Course Description:  A second course in statistical computing, using the SAS
programming language to read data, create and manipulate SAS
data sets, writing and using SAS MACROS, and SAS programming
efficiency. SASbased implementation of Structured Query
Language (SQL). Additional topics may include Hadoop and
parallel computing. 
Oasis Title:  Adv Statistical Programming 
Undergraduate Prerequisite:  STAT 23602360L 
Graduate Prerequisite:  STAT 6220 or STAT 4230/6230 or STAT 6315 or STAT 6420 or STAT 8200 or permission of department 
Semester Course Offered:  Not offered on a regular basis. 
Grading System:  AF (Traditional) 

Course Objectives:  This course will introduce students to the statistical
software package SAS and train them in how to use its DATA
and PROC steps to manipulate and statistically analyze data.
Students who take this course will learn to:
1. Differentiate between a temporary and permanent SAS data set;
2. Identify types of variables;
3. Define the uses of punctuation (semicolon, colon, period) in
SAS;
4. Import raw data files in SAS;
5. Export raw data files in SAS;
6. Combine SAS data sets;
7. Create basic detailed reports using SAS procedures;
8. Create summary reports using SAS procedures;
9. Identify data errors in SAS;
10. Identify syntax errors in SAS;
11. Identify programming logic errors in SAS;
12. Correct data errors in SAS;
13. Correct syntax errors in SAS;
14. Correct programming logic errors in SAS;
15. Outline program steps before writing code;
16. Use advanced DATA step programming statements to solve
problems;
17. Use advanced DATA step efficiency techniques to solve
problems;
18. Write SAS SQL code;
19. Manipulate data using SQL;
20. Query relational databases using SQL;
21. Join tables using SQL;
22. Interpret SAS SQL code;
23. Create SAS macro variables;
24. Use SAS macro variables;
25. Create with the SAS macro facility;
26. Use the SAS macro facility; and
27. Communicate the results of statistical analyses through oral
and written means.
Students will demonstrate competence through individual or
group programming projects, labs, and examinations throughout
the course. 
Topical Outline:  Course topics include accessing data using the DATA step,
managing and manipulating data via DATA step processing,
generating numerical and graphical reports, handling errors,
macro programming and processing, accessing data using SQL and
Hadoop, advanced programming techniques, and programming
efficiency. 
Honor Code Reference:  UGA Student Honor Code: "I will be academically honest in all of
my academic work and will not tolerate academic dishonesty of
others." A Culture of Honesty, the University's policy and
procedures for handling cases of suspected dishonesty, can be
found at www.uga.edu/ovpi. Every course syllabus should include
the instructor's expectations related to academic integrity. 