ST425     
Statistical Inference: Principles, Methods and Computation

This information is for the 2016/17 session.

Teacher responsible

Prof Qiwei Yao COL 7.16

Availability

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.

Teaching

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

Week 11 will be used as a revision week.

Formative coursework

Students will complete weekly assessed problem sheets. They will also complete R practice following instructions from the weekly computing workshop.

Indicative reading

L. Wasserman, All of Statistics.

Y. Pawita, In All Likelihood

K. Knight, Mathematical Statistics

A. Zuur et al., A Beginner's Guide to R. (Available online from LSE Library.)

N. Venables et. al., An Introduction to R (http://cran.r-project.org/doc/manuals/R-intro.pdf)

Assessment

Exam (85%, duration: 3 hours) in the LT week 0.
Project (15%) in the MT.

Student performance results

(2012/13 - 2014/15 combined)

Classification % of students
Distinction 45.7
Merit 20.7
Pass 22.1
Fail 11.4

Key facts

Department: Statistics

Total students 2015/16: 33

Average class size 2015/16: 32

Controlled access 2015/16: No

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
  • Specialist skills