DDMA Level II
Quantitative Modelling Skills cheat sheet
Every chapter's key points, formulas and definitions on one page, for the last week before the exam. Each heading links to the chapter that explains it.
Quantitative modelling concepts
- A model is a simplified representation of a real system, built to understand, predict or optimise its behaviour; a quantitative model expresses it in numbers, variables and equations.
- Building one runs through model type selection, definition and formulation, the target expression type, and the key mathematical functions it relies on.
- A linear model gives one deterministic answer; a probabilistic (stochastic) model builds in randomness and gives a distribution of possible outcomes.
- Quantitative modelling makes assumptions explicit and testable, supports objective comparison of alternatives, and allows what-if analysis without changing the real system.
- The types range from simple analysis and econometric estimation to systems of equations, input-output analysis and partial modelling.
Key terms
- Model
- A simplified representation of a real system, built to understand, predict or optimise its behaviour.
- Quantitative model
- A model expressed in mathematical terms, using numbers, variables and equations rather than qualitative description.
- Linear models
- Represent a relationship as a straight-line function of the inputs.
- Probabilistic (stochastic) models
- Incorporate randomness explicitly, producing a distribution of possible outcomes rather than one fixed answer.
- Regression models
- Estimate the relationship between a dependent variable and one or more predictors (see the chapter on regression modelling).
- Multiple regression
- Regression with more than one predictor variable.
- Line fitting
- Finding the line that best represents a set of data points, the basis of simple linear regression.
- Simple analysis
- Direct calculation from known relationships, without a formal statistical or optimisation model.
- Econometric estimation
- Applying statistical methods (often regression) to economic data to estimate relationships.
- Systems of equations
- Modelling several interacting relationships together, solved simultaneously.
- Input-output analysis
- Models how outputs of one part of a system become inputs to another, common in economic sector analysis.
- Partial modelling
- Models one part of a system in detail while treating the rest as fixed or simplified.
The rest of the sheet covers
- Regression modelling
- Linear programming
- Simulation modelling
- Worked examples
- Exam technique and revision
- Glossary