ST447      Half Unit
Data Analysis and Statistical Methods

This information is for the 2019/20 session.

Teacher responsible

Prof Qiwei Yao


This course is compulsory on the MSc in Data Science and MSc in Operations Research & Analytics. This course is available with permission as an outside option to students on other programmes where regulations permit.

Course not available on MSc in Statistics nor on MSc in Statistics (Financial Statistics) nor on MSc in Statistics (Social Statistics).


Basic knowledge in calculus and linear algebra, as well as a first course in probability and statistics.

Course content

This course provides a comprehensive coverage on some fundamental aspects of probability and statistics. It also covers different aspects of data analysis, including data visualisation and regression. The statistical software R will constitute an integral part of the course, providing hands-on experience of data analysis. 


20 hours of lectures, 5 hours of seminars and 5 hours of computer workshops in the MT.

Week 6 will be used as a reading week.

Formative coursework

Students will be expected to produce 5 exercises in the MT.

The bi-weekly exercises will enable students to learn how to implement statistical methods in R and provide preparation for the project. They will also ensure that students learn about the different methods of statistics and data analysis, as assessed later on the examination. 

Indicative reading

All of Statistics, by Larry Wasserman, Springer.

Data Analysis and Graphics using R: an Example-based Appoach, by John Maindonald an John Braun, Cambridge University Press.


Exam (85%, duration: 2 hours) in the summer exam period.
Coursework (15%) in the MT.

Key facts

Department: Statistics

Total students 2018/19: 31

Average class size 2018/19: 15

Controlled access 2018/19: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Self-management
  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills
  • Specialist skills