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UFMFJR 15 M

UFCFJR-15-M Advanced Statistics

Overview

In this module, students will learn advanced statistical modelling techniques for complex data using modern statistical programming software. This module will cover dimension reduction, data visualisation, supervised and unsupervised learning, in the framework of creating reproducible research.

Objectives

  1. Assess model diagnostics to inform empirical model building
  2. Interpret and explain a wide variety of statistical models in different contexts to both expert and non-expert audiences
  3. Identify appropriate exploratory data analysis techniques and then combine appropriate modelling techniques for a variety of situations
  4. Examine limitations of inference from statistical models based on model evaluation techniques
  5. Produce reproducible statistical research using modern programming tools

Curriculum

Supervised learning

Random Forests

Unsupervised learning (clustering)

Semi-supervised learning

Dimension reduction (Principal Component Analysis/ Factor Analysis)

Variable selection

Visualisation

Assessment

Written assignment (75%)

Practical skills assessment (25%)