Postgraduate Course: SAS Programming for Financial Analysis (CMSE11410)
Course Outline
School | Business School |
College | College of Arts, Humanities and Social Sciences |
Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
SCQF Credits | 10 |
ECTS Credits | 5 |
Summary | SAS software is the standard software used in Financial and Banking industry for analysing and comparing datasets, as well for creating and coding customised models. The aim of this course is to provide students with an introduction to programming in a high-level language, using SAS as an example. Students will acquire hands-on practice on SAS by analysing and manipulating databases. |
Course description |
SAS software is the standard software used in Financial and Banking industry for analysing and comparing datasets, as well for creating and coding customised models. The aim of this course is to provide students with an introduction to programming in a high-level language, using SAS as example. Students will acquire hands-on practice on SAS by analysing and manipulating databases. Students will acquire skills on reading, running, manipulating and creating programs in SAS environment. Good programming practice for sharing their programs with others. Database creation and manipulation. Data analysis and regression via SAS. Introduction to macro language and program development for repetitive analysis.
Outline content:
- Introduction, getting started with SAS
- Reading and creating datasets.
- Combine datasets
- Statistics and Regression
- Introduction to Macro Language
Student Learning Experience:
Students will learn mainly via demonstrations and hands-on exercises. The students will be provided with exercises to practice at home. Evidence of knowledge will consist on an individual piece of code for analysing a real-world dataset.
Tutorial/seminar hours represent the minimum total live hours - online or in-person - a student can expect to receive on this course. These hours may be delivered in tutorial/seminar, lecture, workshop or other interactive whole class or small group format. These live hours may be supplemented by pre-recorded lecture material for students to engage with asynchronously.
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Entry Requirements (not applicable to Visiting Students)
Pre-requisites |
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Co-requisites | |
Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
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Academic year 2021/22, Not available to visiting students (SS1)
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Quota: None |
Course Start |
Semester 2 |
Timetable |
Timetable |
Learning and Teaching activities (Further Info) |
Total Hours:
100
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Seminar/Tutorial Hours 10,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
88 )
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Additional Information (Learning and Teaching) |
Seminar/Tutorial hrs are the min total live hrs, online or in-person, students can expect to receive
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Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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Additional Information (Assessment) |
100% coursework (individual) - assesses all course Learning Outcomes |
Feedback |
Not entered |
No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Know, understand and critically discuss the basics of coding on high-level programming languages.
- Know, understand and critically discuss the role of programming approaches in data analytics.
- Know, understand and critically discuss how programming allow for the creation of customised models and algorithms.
- Apply the main routines available in SAS for data analysis to a range of problems.
- Conceptualise and critically evaluate the structure of estimation commands in standard statistical packages.
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Reading List
Delwiche, L.D. and Slaughter, S.J (2019) The Little SAS Book: A Primer. 6th edition.
Delwiche, L.D, Ottesen, R.A., and Slaughter, S.J. (2020) Exercises and Projects for The Little SAS Book, Sixth Edition.
Resource List:
https://eu01.alma.exlibrisgroup.com/leganto/public/44UOE_INST/lists/29527096080002466?auth=SAML |
Additional Information
Graduate Attributes and Skills |
Cognitive Skills
On completion of the course a student should be able to:
1. Demonstrate a critical understanding of the role of high-level programming language in analytics.
2. Demonstrate a critical understanding of the potential and limitations of high-level programming language.
3. Demonstrate a critical understanding of the aims and potential of data analytics.
4. Demonstrate a high level understanding of the application of programmes to analyse and manage databases.
5. Conceptualise and critically evaluate the structure of estimation commands in standard statistical package.
6. Demonstrate substantial authority and exercise a high level of autonomy and initiative in professional and equivalent activities.
7. Demonstrate leadership and/or originality in tackling and resolving problems and issues.
Subject Specific Skills:
After completing this course, students should be able to:
1. Read, run, manipulate and create programs in a SAS environment,
2. Manipulate programs written by others
3. Input and manipulate data in SAS,
4. Analyse data and estimate regression models using SAS
5. Develop programs in SAS for repetitive analysis
6. Use SAS to analyse and manage databases
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Special Arrangements |
For MSc Finance, Technology and Policy students.
Other Business School students, please contact the Course Secretary. |
Keywords | Not entered |
Contacts
Course organiser | Dr Belén Martín-Barragán
Tel: (0131 6)51 5539
Email: Belen.Martin@ed.ac.uk |
Course secretary | Mrs Kelly-Ann De Wet
Tel: (0131 6)50 8071
Email: K.deWet@ed.ac.uk |
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