[header_logo.jpg]
Home / Services / Clinical Research & Biostatistics / Quantum Institute of Clinical Research & Biostatistics - QICRB / Course Schedule & Registration / Course Details

Course Details

Applied Statistical Analysis Software (SAS) Programming

[register_now_btn.png]
Course ID : QI-APPSAS-201 [same as QI-PRG-201]
Date : Refer dates published above for QI-PRG-201
Location : New Jersey, USA and Bangalore, India (depending on no. of students)
Mode of Training : In-Class
Dates: Instructor Assistance in Classroom : Refer Weekday, Weekend and Evening sessions schedule
Dates: Instructor Access via Email : Post - class access
For Registration/Pricing, call: : Please call our office in New Jersey at 609-454-5635 or email us at info_india@quantument.com for pricing/registration

Description

This course is the first-level course in Statistical Analysis Software (SAS). The course covers essentially computer-based techniques for biomedical researchers that include introduction to SAS from basics through a few advanced topics such as array and macros. Additionally, covers SAS programming methods to clean and validate the data as well as produce data summaries.

Pre-requisite

No prior knowledge of SAS is expected. However, participants are expected to have the knowledge of basic operations of PCs, such as creating folders, accessing files as well as an understanding of basic system commands on your operating systems. Knowledge of Microsoft products such as Excel, Access, Word and PowerPoint is helpful.

Statistical Analysis Software (SAS) is a very powerful and versatile as well as industry-standard statistical tool to manipulate and analyze large research data. This course is the start point for those who want to learn how to write programs in SAS and serves as a prerequisite for other courses.
Learning Outcomes
After completing the course, participants will be able to have a good understanding of the
  • Fundamentals of SAS to develop programs for manipulation and analysis of research data relevant to biomedical research.
  • SAS procedures to clean and validate the data as well as create summary reports of the data.

Topics of Study

  • Getting started

  • Data Step Programming

  • Working With DATE Fields

  • Numerical Functions and Logical Structures

  • Randomization

  • Methods of Getting External Data into SAS Data sets Using Proc IMPORT

  • Working with ARRAYS

  • Modifying and Combining SAS Datasets

  • Macros

  • Basic SAS Procedures to Clean and Validate the Data

  • Graphical and Descriptive Summary of Data Using Various SAS Procedures