ST555 - Statistical Programming I
- Prerequisites: None
- Term & Frequency: Fall, Spring, Summer
- Student Audience: Graduate students seeking an introduction to SAS and R
- Credit: 3 credits
- Recent Texts: None
- Recent Instructors: Jonathan Duggins
- Background and Goals: Computing skills have become increasingly important in our graduate curriculum in Statistics. There is an
increased need to train students to handle the scale and scope of the data facing modern statisticians.
Students must know how to read data from a variety of sources and in a variety of formats, validate
the data for errors, manipulate the data in meaningful ways, subset and group data, merge/append data sets,
and process data in and automated fashion to produce summary reports and to export the
data for statistical analysis.
- Content: An introduction to programming and data management using SAS, the industry standard for statistical practice. Detailed discussion of the program data vector and data handling techniques that are required to apply statistical methods. Topics are based on the current content of the Base SAS Certification Exam and typically include: importing, validating, and exporting of data files; manipulating, subsetting, and grouping data; merging and appending data sets; basic detail and summary reporting; and code debugging. Additional topics with practical applications are also introduced, such as graphics and advanced reporting. Statistical methods for analyzing data are not covered in this course. Regular access to a computer for homework and class exercises is required. Previous exposure to SAS is not expected.
- Alternatives: ST 445. Credit for both ST 445 and ST 555 is not allowed.
- Subsequent Courses: ST 556
SP 2017 Sections:
|001||Duggins,Jonatha||00130 Park Shops||03:00PM-04:15PM||TTh||45/50 - Open||ST555-001|
|601||Duggins,Jonatha||Distance Education-I|| - ||TBA||28/50 - Open||ST555-601|