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Faculty Handbook Archive

Archive Module Description

Department: Mathematical Sciences

MATH3211: PROBABILITY III

Type Level Credits Availability Module Cap Open 3 20 Not available in 2021/22 Durham

Prerequisites

• Complex Analysis II (MATH2011) AND Analysis in Many Variables II (MATH2031) AND Probability II (MATH2647).

• None.

Excluded Combination of Modules

• Probability IV (MATH4131).

Aims

• To build a logical structure on probabilistic intuition, and to cover such peaks of the subject as the Strong Law of Large Numbers and the Central Limit Theorem, as well as more modern topics.

Content

• Introductory examples.
• Coin tossing and trajectories of random walks.
• Discrete renewal theory.
• Limit theorems and convergence.
• Order statistics.
• Non-classical limits and their applications.
• Stochastic order.

Learning Outcomes

Subject-specific Knowledge:
• By the end of the module students will: be able to solve novel and/or complex problems in Probability.
• have a systematic and coherent understanding of theoretical mathematics in the field of Probability.
• have acquired coherent body of knowledge of these subjects demonstrated through one or more of the following topic areas: Probability as a measure.
• Random walks.
• Convergence theorems.
• Discrete renewal theory.
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.
• 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 42 2 per week for 20 weeks and 2 in term 3 1 Hour 42 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: 90%
Element Length / duration Element Weighting Resit Opportunity
Written examination 3 Hours 100%
Component: Continuous Assessment Component Weighting: 10%
Element Length / duration Element Weighting Resit Opportunity
Eight written assignments to be assessed and returned. Other assignments are set for self-study and complete solutions are made available to students. 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