Content (Syllabus outline):
Module 1: Optimization

linear programming
unconstrained optimization of function of several variables
constrained optimization of function of several variables

Module 2: Mathematical modeling

discrete dynamical systems
discrete stochasticity
empirical modeling
continuous models
continuous stochasticity

Module 3: Operations research

other algorithms for linear programming
network optimization models and dynamic programming
nonlinear programming
game theory
decision analysis

Module 4: Probability and statistics

probability and probability distributions
sampling distribution
random variables
central limit theorem
test of statistical hypothesis
estimation of parameters

Module 5: Multivariate analysis

factor analysis
discriminant analysis
cluster analysis
multiple regression
logistic regression
structural equation modeling
time series data analysis

Modul 6: Qualitative data analysis

content analysis method
grounded theory and related grounded analysis
thematizing, coding, categorizing, analysis and interpretation