Prof Gregory Sorkin NAB.3.19

This course is compulsory on the MSc in Management and MSc in Management (CEMS MIM). This course is available on the MPhil/ PhD in Employment Relations & Org Behaviour and MPhil/ PhD in Management. This course is not available as an outside option.

Mathematical modelling and optimisation, particularly linear programming and sensitivity analysis. Introduction to probability including conditional probability, Bayes’ theorem, and essential distributions such as the normal and Poisson distributions. Monte Carlo simulation and Discrete Event Simulation. Decision Analysis, including probabilistic and probability-free approaches, using monetary value or utility. Analysis of Variance, simple and multiple linear regression, including ideas of confounding and statistical control, the use of dummy variables, interactions and non-linear effects of explanatory variables, collinearity, diagnostics and model development. Introduction to logistic regression modelling.

20 hours of lectures and 13 hours and 30 minutes of computer workshops in the MT. 2 hours of lectures in the ST.

Students on this course will have a reading week in Week 6 of MT, in line with departmental policy

Weekly homework and quizzes with periodic formative feedback by Class Teachers. 250-word data analysis project.

Anderson, D.R., Sweeney, Williams, and Wisniewski (2009). An Introduction to Management Science: Quantitative Approaches to Decision Making.

Agresti, A., & B. Finlay. (2009). Statistical Methods for the Social Sciences (Fourth Edition). Pearson.

Anderson, D. R., Sweeney, D. J., Williams, T. A., Freeman, J., & Shoesmith, E. (2014). Statistics for Business and Economics (3rd edition). Cengage.

Exam (85%, duration: 2 hours) in the main exam period.
Project (15%, 500 words) in the MT.

The project is a 500-word data analysis project.