Measure and Integration Theory


Lectures:
Monday 8:00-9:30, HS 3.
Friday 13:15-14:45, HS 13.

Office hours:
Friday 15:00-16:00, Office 09.135.

Description:
The theory of measure and integration belongs to the foundations of modern analysis, and provides the formal framework for probability theory. This course introduces its central concepts and results (discussing in particular: existence, uniqueness, basic properties, and examples of measures; the abstract Lebesgue integral, convergence theorems, and spaces of integrable functions; product measures; measures with densities; applications to real analysis), and offers brief appetizers for some more advanced topics.

Assessment: Written exam (Monday, Feb 05, in HS3).

Bibliography:
[Ax] Sheldon Axler, Measure, Integration & Real Analysis, Graduate Texts in Mathematics (available online).
[Ba] Richard F. Bass, Real Analysis for Graduate Students, Version 4.3 (available online).
[SS] Elias M. Stein and Rami Shakarchi, Real Analysis: Measure Theory, Integration, and Hilbert Spaces, Princeton Lectures in Analysis.


Announcements


Lesson Register



Back