# DEGREE REGULATIONS & PROGRAMMES OF STUDY 2017/2018

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DRPS : Course Catalogue : School of Mathematics : Mathematics

# Undergraduate Course: Data, Algorithms and Decisions (MATH08076)

 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 real-world 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
 Pre-requisites Co-requisites Prohibited Combinations Other requirements Mathematics : Grade A at Highers or A-level
 Pre-requisites None High Demand Course? Yes
 Not being delivered
 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.
 F.S. Hillier and G. J. Lieberman - Introduction to Operations Research, McGraw-Hill Higher Education, 2009 (ISBN: 978-0071324830) H. A. Taha - Operations Research: An Introduction (9th Edition) Pearson, 2010, (ISBN: 978-0132555937) W. L. Winston - Operations Research: Application and Algorithms Brooks/Cole, 1998 (ISBN: 978-0534380588) B. Goldacre - I Think You Will Find It's a Bit More Complicated Than That, Fourth Estate, 2014 (ISBN: 978-0007462483) B. Goldacre - Bad Science, Harper Perennial, 2009 (ISBN: 978-0007284870) D. Cox and C. Donnelly - Principles of Applied Statistics. Cambridge University Press, 2009 (ISBN: 978-1858059082) G. M. Clarke and D. Cooke - A Basic Course in Statistics (5th revised edition), John Wiley, 2004 (ISBN: 978-0340814062)