##
MG4A1

MSc Management pre-sessional: Quantitative Methods and Mathematics

**This information is for the 2013/14 session.**

**Availability**

This course is compulsory on the MSc in Management and MSc in Management (CEMS MIM). This course is not available as an outside option.

**Course content**

The course is divided into two separate subjects: Statistics and Mathematics. The Statistics course covers basic probability and statistics; hypothesis testing; analysis of variance; association, correlation and regression and matrix algebra. The Mathematics course covers the following topics with application reference to economics and business: Linear equations; Algebra and Graphs; Quadratic functions; Indices and Logs; Exponential and natural log; Geometric Series; Derivatives (univariat); Rules of differentiation; Optimisation; Multivariate functions; Unconstraint optimisation; Constraint optimisation; Indefinite integrals; Definite integrals.

**Teaching**

Statistics: 10 x 1 hour lecture (+tutorial) in the three weeks prior to the Michaelmas Term.

Mathematics: 10 x 2 hour lecture (+tutorial) in the three weeks prior to the Michaelmas Term.

**Indicative reading**

Statistics: Huff (1991). How to Lie with Statistics. Penguin. Field, A. (2009). Discovering Statistics using SPSS. 3rd edition. Sage: London. Leik, R. K. (1997). Experimental design and the analysis of variance. Pine Forge Press, Thousand Oaks, CA. Cozby, P & Bates, S. (2012) Methods in Behavioural Research (11th Edition), New York, McGraw-Hill.

Mathematics: Hammond, P and Sydsaeter, K (2002) Essential Mathematics for Economic Analysis Prentice Hall; Jacques, I (2010) Mathematics for Economics and Business, 7th edition Pearson.

**Assessment**

No formal assessment. Students will sit a mock exam at the end of the course based upon the material to aid learning.

** Key facts **

Department: Management

Total students 2012/13: Unavailable

Average class size 2012/13: Unavailable

Value: Non-assessed

**Personal development skills**

- Team working
- Problem solving
- Application of numeracy skills
- Specialist skills