# 4 Classes (41 Units)

**14.12**(12),

**18.06**(12),

**18.200**(5),

**18.600**(12)

# 14.12 Economic Applications of Game Theory

Analysis of strategic behavior in multi-person economic settings. Introduction to solution concepts, such as rationalizability, backwards induction, Nash equilibrium, subgame-perfect equilibrium, and sequential equilibrium, with a strong emphasis on the assumptions behind these solution concepts. Issues of incomplete information, such as signaling and reputation formation. Applications drawn from microeconomics and political economy.

This class has 14.01, and 6.041B as prerequisites.

14.12 will be offered this semester (Fall 2017). It is instructed by M. Yildiz.

Lecture occurs 2:30 PM to 4:00 PM on Tuesdays and Thursdays in E52-164.

This class counts for a total of
12 credits.
This class counts as a **HASS S**.

You can find more information at the http://www.google.com/search?&q=MIT+%2B+14.12&btnG=Google+Search&inurl=https site.

# 18.06 Linear Algebra

Basic subject on matrix theory and linear algebra, emphasizing topics useful in other disciplines, including systems of equations, vector spaces, determinants, eigenvalues, singular value decomposition, and positive definite matrices. Applications to least-squares approximations, stability of differential equations, networks, Fourier transforms, and Markov processes. Uses MATLAB. Compared with 18.700, more emphasis on matrix algorithms and many applications.

This class has 18.02 as a prerequisite.

18.06 will be offered this semester (Fall 2017). It is instructed by S. G. Johnson.

Lecture occurs 11:00 AM to 12:00 PM on Mondays, Wednesdays and Fridays in 54-100.

This class counts for a total of 12 credits.

You can find more information at the http://www.google.com/search?&q=MIT+%2B+18.06&btnG=Google+Search&inurl=https site or on the 18.06 Stellar site.

# 18.200 Principles of Discrete Applied Mathematics

Study of illustrative topics in discrete applied mathematics, including probability theory, information theory, coding theory, secret codes, generating functions, and linear programming. Instruction and practice in written communication provided. Enrollment limited.

This class has 18.06 as a prerequisite.

18.200 will not be offered this semester. It will be available in the Spring semester, and will be instructed by A. Moitra and M. X. Goemans.

This class counts for a total of 5 credits.

You can find more information at the http://www.google.com/search?&q=MIT+%2B+18.200&btnG=Google+Search&inurl=https site.

# 18.600 Probability and Random Variables

Probability spaces, random variables, distribution functions. Binomial, geometric, hypergeometric, Poisson distributions. Uniform, exponential, normal, gamma and beta distributions. Conditional probability, Bayes theorem, joint distributions. Chebyshev inequality, law of large numbers, and central limit theorem. Credit cannot also be received for 6.041A or 6.041B.

This class has 18.02 as a prerequisite.

18.600 will be offered this semester (Fall 2017). It is instructed by J. A. Kelner.

Lecture occurs 10:00 AM to 11:00 AM on Mondays, Wednesdays and Fridays in 54-100.

This class counts for a total of 12 credits.

You can find more information at the http://www.google.com/search?&q=MIT+%2B+18.600&btnG=Google+Search&inurl=https site or on the 18.600 Stellar site.