Course co-ordinator(s): Prof Damian Clancy (Edinburgh), Adrian Turcanu (Dubai), Dr Haslifah Hasim (Dubai).
Aims:
The aim of this course is to learn and apply a range of Statistical Modelling and Analysis techniques applicable for data analysis
Detailed Information
Course Description: Link to Official Course Descriptor.
Pre-requisites: none.
Location: Dubai, Edinburgh.
Semester: 1.
Syllabus:
A practical understanding of:
- Basic probability concepts: Random variables and their distributions; how distributions relate to sampling scenarios.
- Joint distributions, Sums of random variables, Central limit theorems
- Classical inference: Point estimation, moment estimators and maximum likelihood; Confidence intervals – calculation and interpretation; Hypothesis testing and p-values
- Essentials of Bayesian inference: Priors and posteriors; Credible intervals; Predictive distributions
- Modelling approaches: Regression and ANOVA;
- Multivariate exploratory techniques: Principal Components Analysis + Factor Analysis; Introduction to non-parametric methods
- Practical elements in R or Python
SCQF Level: 11.
Credits: 15.