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

Guidelines for interpreting course guide information

Personal development skills

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