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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2020/2021

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DRPS : Course Catalogue : Business School : Common Courses (Management School)

Postgraduate Course: Introduction to SAS (CMSE11210)

Course Outline
SchoolBusiness School CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits0 ECTS Credits0
SummaryThis course develops a student's knowledge and skills in the practical analysis of empirical data.
Course description The aim of the course is to provide an overview of the statistical software SAS, which is widely used by in banking. A particular emphasis is placed on developing the ability to input and manipulate data and to run statistical procedures. A brief introduction to Macro Language and basic coding commands is also included in the course.

The course introduces the statistical software SAS. The course develops computational skills essential to make decisions when working in a bank. The course provides the basic knowledge needed to run programs in a SAS environment, to input and manipulate data, combining and modifying datasets and running statistical procedures using SAS. A basic introduction to coding informatics programs and creating Macro commands will be included.

Syllabus
Introduction, getting started with SAS
Sorting, printing and summarizing
Formats and informats
Manage the variables
Help and General syntax
Plotting and graphics
Macro 1
Macro 2
Linear regression
Merging

Student Learning Experience
During the course, the students will be experiencing a real contact with the statistic software SAS. The program is introduced using a mixture of demonstration, self-learning and practice in the computer laboratory. Students will have a number of exercises to work through during each session and the solutions will be demonstrated. Students may ask questions in the demonstration sessions.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed:
Co-requisites
Prohibited Combinations Other requirements For Business School PG students only, or by special permission of the School. Please contact the course secretary.
Information for Visiting Students
Pre-requisitesBusiness School postgraduate students only.
High Demand Course? Yes
Course Delivery Information
Not being delivered
Learning Outcomes
On completion of this course, the student will be able to:
  1. Know, understand and critically discuss how SAS programs work
  2. Know, understand and critically discuss the main parts of a SAS program
  3. Apply the main routines available in SAS for Data analysis, to a range of problems
  4. Conceptualise and critically evaluate the structure of estimation commands in standard statistical package
Reading List
Recommended:
Lora D. Delwiche and Susan J. Slaughter (2012) The Little SAS Book: A Primer. 5th edition.

Stephen. McDaniel Chris Hemedinger., Hoboken, N.J. SAS for dummies. Wiley Publishing, Inc. ;2010

Further reading:
SAS Institute SAS/STAT User's Guide 9.1.3.
http://support.sas.com/onlinedoc/913/docMainpage.jsp

Cody, Ron (2007) Learning SAS by example: a programmer's guide. SAS Institute.

Resource List:
https://eu01.alma.exlibrisgroup.com/leganto/public/44UOE_INST/lists/18388083900002466?auth=SAML

Additional Information
Graduate Attributes and Skills Cognitive Skills:
After completing this course, students should be able to:
- Read and run programs,
- Manipulate programs written by others
- Create their own programs to save time or modify existing methods
- Implement estimation routines and data summary routines,


Subject Specific Skills:
After completing this course, students should be able to:
- Read, run, manipulate and create programs in a SAS environment,
- Input and manipulate data in SAS,
- Implement estimation routines and data summary routines in SAS,
- Be able to output results in various forms using SAS.
KeywordsSAS
Contacts
Course organiserDr Pawel Orzechowski
Tel:
Email: porzecho@ed.ac.uk
Course secretaryMrs Kelly-Ann De Wet
Tel: (0131 6)50 8071
Email: K.deWet@ed.ac.uk
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