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Durham University

Postgraduate Module Handbook 2021/2022

Archive Module Description

This page is for the academic year 2021-22. The current handbook year is 2022-23

Department: Mathematical Sciences

MATH42420: Topics in Statistics

Type Tied Level 4 Credits 20 Availability Not available in 2021/22
Tied to G1K509 Mathematical Sciences

Prerequisites

  • Statistical Methods.

Corequisites

  • None

Excluded Combination of Modules

  • None

Aims

  • To provide a working knowledge of the theory, computation and practice of a number of specialised statistical tools, complementing Statistical Methods III.

Content

  • Likelihood-based inference
  • Generalised linear models
  • Log-linear modelling of contingency tables
  • Advanced topic: one of multivariate analysis, time series analysis, medical statistics.
  • Reading material in an advanced area of statistics chosen by the lecturer.

Learning Outcomes

Subject-specific Knowledge:
  • By the end of the module students will:
  • be aware of a wide range of applicable statistical methodology.
  • have a systematic and coherent understanding of the theory, computation and application of the mathematics underlying the statistical topics studied.
  • have acquired a coherent body of applicable knowledge on likelihood methods as a general approach to inference.
  • have acquired a coherent body og knowledge of generalised linear methods and log-linear modelling.
  • have a knowledge and understanding of a substantial topic in an advanced area of statistics obtained by independent study.
Subject-specific Skills:
  • In addition students will have specialised mathematical skills in the following areas which can be used with minimal guidance: Modelling, Computation.
Key Skills:

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • Lectures demonstrate what is required to be learned and the application of the theory to practical examples.
  • Computer practicals consolidate the studied material and enhance practical understanding.
  • Assignments for self-study develop problem-solving skills and enable students to test and develop their knowledge and understanding.
  • Formatively assessed assignments provide practice in the application of logic and high level of rigour as well as feedback for the students and the lecturer on students' progress.
  • The end-of-year examination assesses the knowledge acquired and the ability to solve predictable and unpredictable problems.

Teaching Methods and Learning Hours

Activity Number Frequency Duration Total/Hours
Lectures 40 2 per week for 20 weeks (omitting two slots) and 2 in term 3 1 Hour 40
Computer Practicals 2 In unused lecture slots in first two terms 1 Hour 2
Problems Classes 8 Four in each of terms 1 and 2 1 Hour 8
Preparation and Reading 150
Total 200

Summative Assessment

Component: Examination Component Weighting: 100%
Element Length / duration Element Weighting Resit Opportunity
Written examination 3 hours 100%

Formative Assessment:


Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University