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SL 2.6—Modelling skills

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Notes

What is Mathematical Modelling?

Mathematical Model: A mathematical equation or function used to represent and describe a real-world phenomenon or situation.

Mathematical modelling is one of the most powerful tools in applied mathematics. Rather than studying the world directly, we translate a real situation into mathematics, analyse it, and then interpret our findings back in the real-world context.

In SL 2.6, you will develop the skills to:

  • Choose an appropriate model for a given situation
  • Fit the model to data by finding its parameters
  • Test whether the model is reasonable
  • Use the model to make predictions and interpret results
Analogy

Think of a mathematical model like a map. A map is not the actual territory , it simplifies and abstracts reality , but it is still incredibly useful for navigation. Similarly, a mathematical model simplifies a real-world situation but gives us powerful tools to understand and predict it.

The Modelling Process

Mathematical modelling is not a single step , it is a cycle of interconnected stages. Understanding this process will help you structure your work clearly, especially in assessments.

The key stages are:

  1. Identify the problem , What exactly are you trying to model or predict?
  2. Make assumptions and define variables , Simplify the real situation; decide what to include and what to ignore. Define your variables clearly with units.
  3. Formulate the model , Choose an appropriate function type and write the equation.
  4. Solve the mathematical problem , Find parameters, evaluate, calculate.
  5. Interpret the solution , Translate your mathematical answer back into the real-world context.
  6. Validate the model , Check whether the model produces sensible, accurate results against known data.
  7. Refine the model (if necessary) , If the model doesn't fit well, adjust your assumptions or try a different function type.
Note

Modelling is an iterative process. Your first model may not be perfect , that is completely normal. Refinement is a natural and expected part of the process, not a sign of failure.

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← Previous topicSL 2.5—Modelling functionsNext topic →AHL 2.7—Composite functions, finding inverse function incl domain restriction
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