QUANTITATIVE MODELLING SKILLS

❑ Definition of: ✓ Model ✓ Quantitative model ❑ Modelling methodology ✓ Model type selection ✓ Definition and formulation ✓ Target expressions type ✓ Key mathematical functions ❑ Examples of models ✓ Linear models ✓ Probabilistic/stochas tic models ✓ Regression models ✓ Multiple regression ✓ Line fitting\ ❑ Advantages of quantitative modelling ❑ Mathematical modelling paradigms ✓ Differential equations - ordinary differential equations ❑ Types of quantitative modelling ✓ Simple analysis ✓ Econometric estimation ✓ Systems of equations ✓ Input-output analysis ✓ Partial modelling

❑ Definition of regression analysis ✓ Linear regression ✓ Multiple linear regression ✓ Non-linear regression ❑ Linear regression model assumptions ❑ Simple linear regression model ❑ Multiple linear regression model ❑ Obtaining dataset from appropriate sources ❑ Choosing the best regression model ❑ Regression analysis in spreadsheets ❑ Interpreting regression analysis results ✓ Interpret p-values ✓ Coefficients in regression analysis ❑ Advantages and disadvantages of ❑ Linear regression

❑ Linear programming ❑ Constrained optimization models ✓ Decision variables ✓ Objective function ✓ Constraints: ✓ Non-negativity restriction ❑ Advantages and disadvantages of using optimization models ❑ Linear programming process ❑ Assumptions of linear programming models ❑ Solve linear program ✓ Graphical method ✓ Using r ❑ Using ms excel

❑ Concepts of modelling & simulation ✓ Models and events ✓ System state variables ✓ Classification of models ❑ Definition of: ❑ Simulation ❑ Modelling ❑ Principles for simulation modelling And experimentation ❑ The modelling process ❑ Monte carlo / risk analysis Simulation ❑ Agent-based modelling and Simulation ❑ Discrete event simulation ❑ System dynamics simulation ❑ Solutions ❑ Developing simulation models ❑ Simulation models components ❑ Input variables, ❑ Performance measures ❑ Functional relationships ❑ Simulation model procedure ❑ Performing simulation analysis ❑ Procedure ❑ The modelling process ❑ Verification and validation ❑ Modelling and simulation ✓ Continuous ✓ Discrete system simulation ✓ Monte carlo simulation ✓ Database ❑ Modelling and simulation ✓ Advantages and disadvantages ❑ Application areas