Difference between revisions of "Math 544: Advanced Probability 2"

From MathWiki
Jump to: navigation, search
 
(21 intermediate revisions by 2 users not shown)
Line 8: Line 8:
  
 
=== Prerequisite ===
 
=== Prerequisite ===
[[Math 214]] or equivalent.
+
[[Math 543]].
 +
 
 +
=== Recommended ===
 +
[[Math 341]], [[Math 342|342]], Stat 441(?); or equivalents.
  
 
=== Description ===
 
=== Description ===
Probability theory and its applicationsTopics include random variables,
+
Advanced concepts in modern probabilityConvergence theorems and laws of large numbers.  Stationary processes and ergodic theorems.  Martingales.  Diffusion processes and stochastic integration.
independence and conditioning, laws of large numbers, random walks, martingales, Markov chains, renewal processes, ergodic theorems, Brownian motion, and stochastic integration.
+
  
 
== Desired Learning Outcomes ==
 
== Desired Learning Outcomes ==
  
 
=== Prerequisites ===
 
=== Prerequisites ===
 +
This course has [[Math 543]] as a prerequisite, so it can build on the work done in that class.
  
 
=== Minimal learning outcomes ===
 
=== Minimal learning outcomes ===
 +
Outlined below are topics that all successful Math 544 students should understand well. As evidence of that understanding, students should be able to demonstrate mastery of all relevant vocabulary, familiarity with common examples and counterexamples, knowledge of the content of the major theorems, understanding of the ideas in their proofs, and ability to make direct application of those results to related problems.
  
 
<div style="-moz-column-count:2; column-count:2;">
 
<div style="-moz-column-count:2; column-count:2;">
 
+
# Convergence of random variables
 +
#* Almost sure
 +
#* In probability
 +
#* In mean
 +
#* In distribution
 +
# Laws of Large Numbers
 +
#* Weak Law
 +
#* Strong Law
 +
# Stochastic processes
 +
#* Gaussian
 +
#* Stationary
 +
#* Stationary increments
 +
#* Independent increments
 +
#* Filtrations
 +
#** Adapted processes
 +
#** Predictable processes
 +
#** Stopping times
 +
# Ergodic theory
 +
#* Birkhoff's Ergodic Theorem
 +
#* Mixing
 +
# Martingales
 +
#* Submartingales and supermartingales
 +
#* Doob Decomposition Theorem
 +
#* Optional Stopping Theorem
 +
#* Optional Sampling Theorem
 +
#* Martingale Convergence Theorem
 +
#* Convergence of backwards martingales
 +
# Brownian motion
 +
#* Definition
 +
#* Existence
 +
#* Path properties
 +
# Itô integral
 +
#* With respect to Brownian motion
 +
#* With respect to diffusion processes
 +
#* Itô formula<br><br><br><br><br><br>
 
</div>
 
</div>
 +
 +
=== Textbooks ===
 +
Possible textbooks for this course include (but are not limited to):
 +
 +
* Achim Klenke, ''Probability Theory:  A Comprehensive Course'', Springer, 2008.
  
 
=== Additional topics ===
 
=== Additional topics ===
Line 28: Line 71:
 
=== Courses for which this course is prerequisite ===
 
=== Courses for which this course is prerequisite ===
  
[[Category:Courses|544]]
+
None

Latest revision as of 16:28, 29 March 2018

Catalog Information

Title

Advanced Probability 2.

Credit Hours

3

Prerequisite

Math 543.

Recommended

Math 341, 342, Stat 441(?); or equivalents.

Description

Advanced concepts in modern probability. Convergence theorems and laws of large numbers. Stationary processes and ergodic theorems. Martingales. Diffusion processes and stochastic integration.

Desired Learning Outcomes

Prerequisites

This course has Math 543 as a prerequisite, so it can build on the work done in that class.

Minimal learning outcomes

Outlined below are topics that all successful Math 544 students should understand well. As evidence of that understanding, students should be able to demonstrate mastery of all relevant vocabulary, familiarity with common examples and counterexamples, knowledge of the content of the major theorems, understanding of the ideas in their proofs, and ability to make direct application of those results to related problems.

  1. Convergence of random variables
    • Almost sure
    • In probability
    • In mean
    • In distribution
  2. Laws of Large Numbers
    • Weak Law
    • Strong Law
  3. Stochastic processes
    • Gaussian
    • Stationary
    • Stationary increments
    • Independent increments
    • Filtrations
      • Adapted processes
      • Predictable processes
      • Stopping times
  4. Ergodic theory
    • Birkhoff's Ergodic Theorem
    • Mixing
  5. Martingales
    • Submartingales and supermartingales
    • Doob Decomposition Theorem
    • Optional Stopping Theorem
    • Optional Sampling Theorem
    • Martingale Convergence Theorem
    • Convergence of backwards martingales
  6. Brownian motion
    • Definition
    • Existence
    • Path properties
  7. Itô integral
    • With respect to Brownian motion
    • With respect to diffusion processes
    • Itô formula





Textbooks

Possible textbooks for this course include (but are not limited to):

  • Achim Klenke, Probability Theory: A Comprehensive Course, Springer, 2008.

Additional topics

Courses for which this course is prerequisite

None