# Applied Math

I can remember the first time math became really interesting to me. It was a university class on Linear Programming. It was then that I realized real-world problems that seemed too complicated to even begin contemplating, could be translated into math problems and solved. Since then, my respect and love for applied math has grown tremendously. I don’t claim to be a mathematician and I continue to struggle with the more advanced concepts. However, because I understand its vast potential, I am more than willing to struggle with it until my brain aches and I finally get it.

I have taken bachelors and masters-level courses in the following areas:

- Optimization
- Linear Programming
- Non-Linear Programming
- Integer Programming
- Goal Programming
- Simulation
- Monte Carlo Simulation
- Discrete-event Simulation
- Statistics
- ANOVA, ANCOVA
- MANOVA, MANCOVA
- Factor Analysis
- Principle Components Analysis
- Multiple Discriminant Analysis
- Cluster Analysis
- Canonical Correlation Analysis
- Forecasting (single time-series)
- Linear and Non-Linear Regression
- using Least Squares methods
- using Maximum Likelihood methods
- Calculus
- simple differential
- simple integral

My masters research also uses the following techniques:

- Multi-Criteria Decision Making
- Analytical Hierarchy Process
- Analytical Network Process
- Cluster Analysis
- Association Rule Learning (a common data-mining method)

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