Introduction to software tools for modeling and data analysis Exposure to computational software for optimization. Use of some software tools such as AMPL/ CPLEX/ Spreadsheet Solver/ LINDO/ LINGO/ Neos Solver/ MATLAB for solving and analyzing optimization problems. Building models, representing input data, results, interpretation & sensitivity analysis. Exposure to statistical packages for data analysis. Use of R/ SAS/ SPSS/ Excel-spreadsheet. Summarizing data with descriptive statistics, computing statistics, statistical estimation & tests Notion of simulation and effect of randomness. Introduction to Monte Carlo simulation. Simulation of reliability, inventory, queueing systems and basic Markov models, computing performance measures.