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The University of Southampton

MANG2062 SAS Base Programming

Module Overview

This course provides part of the essential knowledge and skills required for conducting the Final Project module in the final year. SAS (Statistical Analysis System) is the leading data analytics software package. This module will cover the fundamentals of SAS base programming. On successful completion of this module, you will be able to use SAS software to read data, access, manage and manipulate ‘big’ data, solve problems, save programs and datasets, use conditional logic, combine files, produce tables and listings of data, and use data analysis techniques. The module will also help prepare you for the SAS Base programming certification.

Aims and Objectives

Learning Outcomes

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

  • key computer programming concepts for managing and analysing ‘big data’;
  • the SAS Base language and how it is used to manage, analyse and report data.
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • read structured and unstructured data stored in popular formats such as excel worksheets, text tables into SAS;
  • store data in SAS libraries;
  • manipulate, analyse, visualize and report data using SAS.
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • use your analytic skills in problem solving;
  • communicate technical ideas to non-specialist managers.


The topics covered in this module will include: • Overview of SAS: Submitting SAS programs, Working with SAS syntax and SAS libraries • Introduction to reading data and adding attributes: Reading Excel worksheets, Reading delimited raw data files • Manipulating data in SAS: Combining SAS Datasets, Producing Summary Reports, Enhancing Reports using Global statements and using ODS, Outputting to multiple datasets or observations • Reading Raw Data Files with input controls: Data Transformations-manipulating character and numeric values, Debugging Techniques- putlog and debug • Processing Data Iteratively- Do loops and Arrays, Restructuring a Data Set with rotate and transpose, Analysing relationships among variables: proc corr, regression and logistic

Learning and Teaching

Teaching and learning methods

Teaching methods include: • Lectures • Interactive case studies • Computer labs • Directed reading • Private/guided study Learning activities include: • Introductory lectures • 2 assignments (individual written coursework) • Case study • In class debate and discussion • Private study • Use of video and online materials

Completion of assessment task48
Wider reading or practice30
Preparation for scheduled sessions12
Practical classes and workshops12
Total study time150

Resources & Reading list

Sas Institute (2011). SAS Certification Prep Guide: Base Programming for SAS 9. 

Peng, J.C.Y. (2009). Data Analysis Using SAS. 



In-class activities


MethodPercentage contribution
Data analysis project 80%
Program 20%


MethodPercentage contribution
Data analysis project 100%


MethodPercentage contribution
Data analysis project 100%

Repeat Information

Repeat type: Internal & External

Linked modules

Prerequisites: (MANG1007 or MANG1019) and MANG1022


Costs associated with this module

Students are responsible for meeting the cost of essential textbooks, and of producing such essays, assignments, laboratory reports and dissertations as are required to fulfil the academic requirements for each programme of study.

In addition to this, students registered for this module typically also have to pay for:


Recommended texts for this module may be available in limited supply in the University Library and students may wish to purchase the mandatory/additional reading text as appropriate.

Please also ensure you read the section on additional costs in the University’s Fees, Charges and Expenses Regulations in the University Calendar available at

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