# MTH4099 - Measure theory - 2019

## Undergraduate, Postgraduate - Unit

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.

Faculty

Science

Organisational Unit

School of Mathematical Sciences

Chief examiner(s)

Coordinator(s)

Unit guides

Offered

Clayton

• First semester 2019 (On-campus)

Prerequisites

Enrolment in the Master of Mathematics

MTH3140

Prohibitions

MTH5099

## Synopsis

Measure theory is one of the few theories which permeates all core mathematical domains (pure, applied and statistics). We develop Lebesgue integration and probability theory from the core elements of measure theory. The initial background will be kept to a minimum. In particular, it is only required knowledge of real analysis and elementary probability theory (prior knowledge of functional analysis is not required, but it is definitely encouraged). On the other hand, the topics covered in this course will be fundamental for the understanding of advanced courses (differential geometry, advanced analysis, partial differential equations), as described above.

The unit will cover such pure topics as: semi-rings, algebras, and sigma-algebras of sets, measures, outer measures, the Lebesgue and Borel measures, construction of Vitali sets, measurable and integrable functions, the Lebesgue integral and the fundamental theorems, the Lebesgue spaces, iterated measures and the Fubini theorem, modes of convergence, signed measures, decomposition of measures and the Radon-Nikodym theorem, approximation results for the Lebesgue measure.

The unit will also cover topics which are essential for probability theory: such as Borel-Cantelli Lemma, independence, Kolmogorov 0-1 law, exponential bounds, conditional expectation, martingales.

## Outcomes

On successful completion of this unit, students will be able to:

1. Formulate complex problems using appropriate measure theory terminology.
2. Use sophisticated tools from measure theory in various areas of Mathematics (e.g. partial differential equations, geometric analysis, dynamical systems, general relativity, probability theory).
3. Identify specific situations to which the fundamental results of measure theory apply, and demonstrate advanced expertise in applying these results to said situations.
4. Communicate complex results and specialised information using the language of measure theory.

## Assessment

Examination (3 hours): 60% (Hurdle)

Continuous assessment: 40%

Hurdle requirement: To pass this unit a student must achieve at least 50% overall and at least 40% for the end-of-semester exam.

## Workload requirements

3 hours of lectures and 1h of tutorial per week.

8 hours independent study per week.

See also Unit timetable information

## This unit applies to the following area(s) of study

Master of Mathematics