Statistical Inference: Principles, Methods and Computation

This information is for the 2013/14 session.

Teacher responsible

Prof Qiwei Yao COL 7.16


This course is compulsory on the MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (Research) and MSc in Statistics (Research). This course is available on the MSc in Social Research Methods. This course is available with permission as an outside option to students on other programmes where regulations permit.

Course content

The course will provide a comprehensive coverage on some fundamental aspects of probability and statistics methods and principles. It also covers linear regression analysis. Data illustration using statistical package R constitutes an integral part throughout the course, therefore provides the hands-on experience in simulation and data analysis.


40 hours of lectures, 10 hours of seminars and 10 hours of computer workshops in the MT.

Formative coursework

Students will be expected to produce 1 project in the MT.

Weekly assessed problem sheets.

Indicative reading

L. Wasserman, All of Statistics.
Y. Pawita, In All Likelihood
K. Knight, Mathematical Statistics
W. N. Venables and B. D. Ripley, Modern Applied Statistics with S
N. Venables et. al., An Introduction to R (


Exam (85%, duration: 3 hours) in the main exam period.
Project (15%) in the MT.

Key facts

Department: Statistics

Total students 2012/13: 43

Average class size 2012/13: 88

Value: One Unit

Guidelines for interpreting course guide information

Personal development skills

  • Leadership
  • Self-management
  • Team working
  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills