Undergraduate Course: Data, Algorithms and Decisions (MATH08076)
Course Outline
School  School of Mathematics 
College  College of Science and Engineering 
Credit level (Normal year taken)  SCQF Level 8 (Year 1 Undergraduate) 
Availability  Available to all students 
SCQF Credits  20 
ECTS Credits  10 
Summary  The course focuses on applications, with case studies of realworld problems and data, and guest lectures from practitioners from inside and outside the university. 
Course description 
1. Data : Graphical and tabular presentations and inferential reasoning from data. Areas of application that could be included are gene expressions; forensic statistics; extremes; ecology; environment; astronomy; medicine and biology.
2. Algorithms : The idea of an algorithm, representation of algorithms, importance of execution speed and memory usage. Examples to come mainly from section 3 below.
3. Decisions : Fundamentals of Operational Research / Decision Mathematics in wide use in the modern world with an emphasis on mathematical modelling of real world problems, ie., translating decision making problems into the mathematical language. The ideas will be applicable in numerous sectors in the economy including but not limited to airlines, healthcare, travel, telecommunication and entertainment.
Data :
1. Graphical and Tabular Representations of Data
2. Descriptive Statistics
3. Samples and Populations
4. Inference
5. Applications
Decisions and Algorithms :
6. Mathematical Modelling for Decision Making
7. Graphical Approach to Linear Programming
8. Integer Constraints
9. Algorithms
10. Nonlinear Optimization: Basics and Algorithms

Entry Requirements (not applicable to Visiting Students)
Prerequisites 

Corequisites  
Prohibited Combinations  
Other requirements  Mathematics : Grade A at Highers or Alevel 
Information for Visiting Students
Prerequisites  None 
High Demand Course? 
Yes 
Course Delivery Information
Not being delivered 
Learning Outcomes
On completion of this course, the student will be able to:
 The ability to translate decision making problems and problems involving data to mathematical language.
 The ability to use basic graphical and tabular methods for presentation of data and their interpretation.
 The ability to select and use appropriate algorithms to solve real world problems.
 The ability to use of spreadsheet applications and specialized software (such as R) to solve optimization and statistical problems.

Reading List
F.S. Hillier and G. J. Lieberman  Introduction to Operations Research, McGrawHill Higher Education, 2009 (ISBN: 9780071324830)
H. A. Taha  Operations Research: An Introduction (9th Edition) Pearson, 2010, (ISBN: 9780132555937)
W. L. Winston  Operations Research: Application and Algorithms Brooks/Cole, 1998 (ISBN: 9780534380588)
B. Goldacre  I Think You Will Find It's a Bit More Complicated Than That, Fourth Estate, 2014 (ISBN: 9780007462483)
B. Goldacre  Bad Science, Harper Perennial, 2009 (ISBN: 9780007284870)
D. Cox and C. Donnelly  Principles of Applied Statistics. Cambridge University Press, 2009 (ISBN: 9781858059082)
G. M. Clarke and D. Cooke  A Basic Course in Statistics (5th revised edition), John Wiley, 2004 (ISBN: 9780340814062) 
Additional Information
Graduate Attributes and Skills 
Not entered 
Keywords  DAD 
Contacts
Course organiser  Dr Burak Buke
Tel: (0131 6)50 5086
Email: b.buke@ed.ac.uk 
Course secretary  Ms Louise Durie
Tel: (0131 6)50 5050
Email: L.Durie@ed.ac.uk 

