Statistics 3I: Inference STATS3015

  • Academic Session: 2019-20
  • School: School of Mathematics and Statistics
  • Credits: 10
  • Level: Level 3 (SCQF level 9)
  • Typically Offered: Semester 1
  • Available to Visiting Students: Yes
  • Available to Erasmus Students: Yes

Short Description

To introduce students to the fundamental principles of likelihood-based inference, with emphasis on the large sample results that are widely used in practice.

Timetable

Lectures: 2 hours per week (at times to be arranged)

Tutorials: fortnightly (at times to be arranged)

Requirements of Entry

The normal requirement is that students should have been admitted to the third year of a Designated Degree programme in Statistics.

Excluded Courses

Inference 3 [STATS4012]

Statistical Inference (Level M) [STATS5028]

Co-requisites

The courses prescribed in the Designated Degree programme to which the student has been admitted.

Assessment

90-minute, end-of-course examination (100%)

Main Assessment In: April/May

Course Aims

The aim of this course is:

■ To introduce students to the fundamental principles of likelihood-based inference, with emphasis on the large sample results that are widely used in practice.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

■ write down the likelihood, given a description of a model;

■ perform likelihood based inference for a variety of simple statistical models;

■ maximise likelihoods for simple models numerically;

■ perform interval estimation and perform hypothesis tests for parameters in simple models;

■ sketch what constitute the 'good' properties of estimation, testing and interval estimation procedures;

■ apply the bootstrap technique to practical problems where information on the variability of estimates is required.

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.