Course Description

This class is designed to give students the necessary tools to manipulate and/ or restructure a certain dataset before it can be analyzed using one of the statistical procedures. This course is essential for database management. Students can use SAS to analyze data for their poster presentations, thesis projects, peer-reviewed journal articles, and job internships.

• Transform a raw data file into a SAS file (using different input styles) which is ready for analysis by the SAS statistical procedures,
• Access external raw data sets and SAS data sets,
• Create a temporary and a permanent SAS data sets,
• Import data from other programs such as excel,
• Reshape datasets whose structure does not conform to that which will be needed for a certain analysis,
• Merge data sets that come from 2 or more sources,
• Create new variables and modify existing ones,
• Learn the SAS functions and the date functions,
• Understand conditional processing and program flow (i.e. make effective use of the if-then-else statements),
• Write simple algorithms, which make use of logical statements, in conjunction with standard programming tools, such as DO LOOPS and ARRAYS,
• Create multiple records per subject (wide to long dataset),
• Dressing and formatting SAS output,
• Program some basic statistical procedures or SAS PROCS such as t-tests, ANOVA, chi-square tests, correlation, linear regression, logistic regression, and Cox proportional hazards model, and
• Students are expected to use the SAS tools they learned during this course, apply them using different data sets, and write their own SAS programs to answer a specific hypothesis they need to test.