Durham University
Programme and Module Handbook

Undergraduate Programme and Module Handbook 2018-2019 (archived)

Module MATH4071: Topics in Statistics IV

Department: Mathematical Sciences

MATH4071: Topics in Statistics IV

Type Open Level 4 Credits 20 Availability Available in 2018/19 Module Cap Location Durham

Prerequisites

  • Statistical Methods III (MATH 3051).

Corequisites

  • None.

Excluded Combination of Modules

  • Topics in Statistics III (MATH 3361).

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:

    Eight written or electronic assignments to be assessed and returned. Other assignments are set for self-study and complete solutions are made available to students.

    ■ 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