The areas covered in this module include probability theory, likelihood, common distributions, confidence intervals, hypothesis tests, parametric and non-parametric tests.
Upon successful completion of this module, you will be able to:
- demonstrate the ability to critically appraise and evaluate mathematical and statistical techniques for the given empirical/data analysis.
- understand the physical significance of the given mathematical and statistical technique.
- use the optimisation techniques in decision making.
- use the statistically significant conclusions from the sample data.
- Review of differential calculus
- Vectors and matrices
- Geometry of matrices and derivatives: linear transformations and partial derivatives
- Descriptive Statistics: Data and Data Presentation, Measures of Location and Variability
- Probability Theory
- Probability Distributions
- Sampling Distributions
- Statistical Significance and Tests of Hypothesis
- Analysis of Variance
- Linear Regression and Correlation
15 (150 hours)
- Summative coursework (30%)
- Written examination (70%)