Aims & Learning Objectives:
Aims: To teach the basic ideas of probability, data variability, hypothesis testing and of relationships between variables and the application of these ideas in management.
Objectives:
Students should be able to formulate and solve simple problems in probability including the use of Bayes' Theorem and Decision Trees. They should recognise real-life situations where variability is likely to follow a binomial, Poisson or normal distribution and be able to carry out simple related calculations. They should be able to carry out a simple decomposition of a time series, apply correlation and regression analysis and understand the basic idea of statistical significance.
Content:
The laws of Probability, Bayes' Theorem, Decision Trees.
Binomial, Poisson and normal distributions and their applications; the relationship between these distributions.
Time series decomposition into trend and season al components; multiplicative and additive seasonal factors.
Correlation and regression; calculation and interpretation in terms of variability explained. Idea of the sampling distribution of the sample mean; the Z test and the concept of significance level.
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