This course covers, as the name might suggest, some topics in analysis. It assumes some basic familiarity with analysis and a little experience with metric spaces.
This course is an introduction to measure theory, especially as it applies to probability. It assumes you have previously taken a second-year undergraduate course in real analysis.
This course covers several topics from number theory, and assumes only basic knowledge (Euclid's algorithm, prime numbers, etc.)
This course is an introduction to the theory of finite undirected graphs.
This course covers topics around the theory of communication, and assumes (a little) knowledge of algebra and probability.
The Applied Probability course deals mostly with the theory of continuous-time Markov chains, and assumes that you have already taken an undergraduate course on discrete-time Markov chains.
The course is divided into sections:
1. Basic aspects of continuous-time Markov chains
2. Qualitative properties of continuous-time Markov chains (hitting times, transience/recurrence, equilibrium distributions)
3. Queueing theory
4. Renewal theory
5. Population genetics
These cards contain definitions, statements and proofs of theorems from the course.
The information come from diverse books, online etc.
The Multiplication Table is from 1 to 12.
• Card type: Cloze deletion
• Tags: Multiplication Table
• Last updated: 18-Jul-14
Textbook used is Jon Rogawski's "Calculus: Second Edition."
The multiplication table from 3x3 to 9x9.