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Module

MAS8905 : Statistical Inference (Inactive)

  • Inactive for Year: 2024/25
  • Module Leader(s): Dr Dennis Prangle
  • Owning School: Mathematics, Statistics and Physics
  • Teaching Location: Newcastle City Campus
Semesters

Your programme is made up of credits, the total differs on programme to programme.

Semester 1 Credit Value: 10
ECTS Credits: 5.0
European Credit Transfer System

Aims

To gain an understanding of some of the principles of statistical inference and associated results in probability. This will deepen understanding of the fundamental precepts of inference and facilitate the assimilation of more advanced practical methodology, especially for the case when there are multidimensional parameters.

Module summary
The course builds on the foundations of inference laid in MAS2901. A variety of types of methods for inference for models with multiple parameters are established, including asymptotic methods for large samples, exact methods and computer-intensive approaches.

Outline Of Syllabus

The multivariate Normal distribution and its principal properties, especially as they relate to asymptotic likelihood methods. Maximum likelihood for multi-parameter models, including asymptotic methods for interval estimation and hypothesis testing. Revision of the idea of sufficiency and the factorization theorem and application to Cramer-Rao lower bounds and the Rao-Blackwell theorem. The bootstrap and its use to compute standard errors and interval estimates.

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion113:0013:00Revision for unseen exam
Guided Independent StudyAssessment preparation and completion12:002:00Unseen exam
Scheduled Learning And Teaching ActivitiesLecture31:003:00Problem classes
Scheduled Learning And Teaching ActivitiesLecture21:002:00Revision lectures
Scheduled Learning And Teaching ActivitiesLecture251:0025:00Formal lectures
Guided Independent StudyIndependent study26:0012:00Preparation for written assignments
Guided Independent StudyIndependent study122:0022:00Studying, practising and gaining understanding of course material
Guided Independent StudyIndependent study33:009:00Review of written assignments and class test
Guided Independent StudyIndependent study112:0012:00Preparation for class test
Total100:00
Jointly Taught With
Code Title
MAS3905Statistical Inference
Teaching Rationale And Relationship

Lectures are used for the delivery of theory and explanation of methods, illustrated with examples, and for giving general feedback on marked work. Problem Classes are used to help develop the students’ abilities at applying the theory to solving problems. Tutorials are used to identify and resolve specific queries raised by students and to allow students to receive individual feedback on marked work. In addition, office hours (two per week) will provide an opportunity for more direct contact between individual students and the lecturer.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Exams
Description Length Semester When Set Percentage Comment
Written Examination1201A90N/A
Written Examination401M5Class test
Exam Pairings
Module Code Module Title Semester Comment
Statistical Inference1N/A
Other Assessment
Description Semester When Set Percentage Comment
Written exercise1M5Two written assignments
Assessment Rationale And Relationship

A substantial formal unseen examination is appropriate for the assessment of the material in this module. The written exercises are expected to consist of two assignments of equal weight: the exact nature of assessment will be explained at the start of the module. The exercises and the in-course test allow the students to develop their problem solving techniques, to practise the methods learnt in the module, to assess their progress and to receive feedback; these assessments have a secondary formative purpose as well as their primary summative purpose.

Reading Lists

Timetable