# Math 210 schedule

Tuesday Thursday
Jan. 9

No class
Jan. 11

In Lecture:
• Overview of the course
• Two person games and the media: Why is lying on the rise?
• Strategies in two person games

• On Bullshit (entire book)
• FAPP = For all Practical Purposes, Chapter 15.1
• How math can save your life, chapter 2. Here is an excerpt which describes two person game zero sum game theory. The recipe for determining optimal strategies for such games is described on pages 31 - 32.
• Pages 736-739 of Raghavan's article on zero sum two person games

Homework:
A nice example of B.S.
Jan. 16

In Lecture:
• B.S. versus lying, examples from the news.
• Two person zero sum games, continued. Examples involving credibility and the lying benefit.

• On Bullshit (entire book)
• FAPP = For all Practical Purposes, Chapter 15.1
• How math can save your life, chapter 2. Here is an excerpt which describes two person game zero sum game theory. The recipe for determining optimal strategies for such games is described on pages 31 - 32.
• Pages 736-739 of Raghavan's article on zero sum two person games

Jan. 18

In Lecture:
• Recap of analysis of the truth versus lying game
• Why the lying benefit is necessary to explain speakers who always lie
• Extremism
• Multi-option, two person zero sum games
• Dominant strategies, maximins, minimaxes and saddlepoints
• Why speaking bullshit and expecting bullshit form a saddlepoint in the absence of credibility.

• On Bullshit (entire book)
• FAPP = For all Practical Purposes, Chapter 15.1
• How math can save your life, chapter 2. Here is an excerpt which describes two person game zero sum game theory. The recipe for determining optimal strategies for such games is described on pages 31 - 32.
• Pages 736-739 of Raghavan's article on zero sum two person games

Homework:
Jan. 23

In Lecture:
• Proof that maximin <= minimax
• Proof that for a two person two option zero sum game, a dominant strategy exists if and only if there is a saddlepoint. This is not true of larger games.
• For arbitrary zero sum games, if there is a dominant strategy there is a saddlepoint.

• On Bullshit (entire book)
• FAPP = For all Practical Purposes, Chapter 15.1
• How math can save your life, chapter 2. Here is an excerpt which describes two person game zero sum game theory. The recipe for determining optimal strategies for such games is described on pages 31 - 32.
• Pages 736-739 of Raghavan's article on zero sum two person games

Homework:
Jan. 25

In Lecture:
• Proof of the recipe for finding optimal strategies in a two-person two-option zero sum game

• On Bullshit (entire book)
• FAPP = For all Practical Purposes, Chapter 15.1
• How math can save your life, chapter 2. Here is an excerpt which describes two person game zero sum game theory. The recipe for determining optimal strategies for such games is described on pages 31 - 32.
• Pages 736-739 of Raghavan's article on zero sum two person games

Jan. 30

In Lecture:
• Three by three games
• The three planes arising from the rock paper scissors game. The lower left corner is at the point (p_1,p_2,z) = (0,0,-1). The three planes are the graphs of the functions giving the expected payoff as a function of (p_1,p_2,1-p_1-p_2) played by player 1 against the three pure strategies of player 2.
• Linear programming problems

• Feb. 1

In Lecture:
• Linear programming problems: Real world examples.
• Statement of how optimal game theory strategies relate to linear programming

Video of class (downloadable) - to be posted
Feb. 6

No in class meeting today. Instead, please have a look at this Video (downloadable) giving an example of how to find optimal strategies via linear programming and the use of vertices.

Note: Skype office hours will be at 10 p.m. tonight. Please send ted an e-mail if you could like to be part of these office hours.
Feb. 8
• No class: Cancelled due to the Eagles parade!
• Feb. 13

In Lecture
Feb. 15

In Lecture
• The Rock Paper Scissors game via linear programming
• Polynomial time problems

Feb. 20

In Lecture
Feb. 22

In Lecture
• End of the proof that linear programming problems have solutions.

Feb. 27

In Lecture
March 1

In Lecture
• First mid-term exam

March 13

In Lecture
March 15

In Lecture:
• End of the proof that one can solve linear programming problems using vertices
• Zombie epidemic models

March 20

In Lecture:
• Zombie epidemic models, continued
• Autonomous ordinary differential equations

March 22

In Lecture:
• Using matrix exponentials to find explicit solutions of autonomous systems of ordinary differential equations
• Stability and linear stability of ordinary differential equations
• Eigenvalues of matrices

March 27

In Lecture:
• Jordan canonical forms and their exponentials
• Testing when two by two matrices have eigenvalues with negative real parts
• Equilibria of the updated zombie model

March 29

In Lecture:
• Stability analysis of the updated zombie model

April 3

In Lecture:
• Completion of the analysis of the updated zombie model
• Beginning of Probability theory
• Calculation of probabilities for finite sample spaces by counting and combinatorics

April 5

In Lecture:
• Using maple to plot vector fields
• Permuations and Combinations
• Multinomial theorem
• Sigma-algebras and the borel subsets of the real numbers
• Probability density functions

April 10

In Lecture:
• Review for the mid-term: Autonomous differential equations, stability and linear stability, modeling.
• Conditional probability
• Bayes theorem
• Updating prior estimates of probabilities using new observations

April 12

In Lecture:
• Second mid-term
April 17

In Lecture:
• Indpenedent events
• Random variables
• Density functions and distribution functions
• Expectations and standard deviations
• Constructing new random variables from old ones