Back to Mathematical Modelling

Higher Applications of Mathematics

Mathematical Modelling reference

Quick reference cards for variables, formulae, model types, units, error, tolerance, assumptions and limitations.

Variable

A quantity that can change in a model.

Use when

Use variables to describe inputs and outputs clearly.

Key method

Choose a letter and define it with units.

Example

Let d be distance travelled in miles.

Formula

A rule connecting variables.

Use when

Use when the relationship between quantities is known.

Key method

Substitute known values, then calculate the unknown value.

Example

cost = 0.18 × units used.

Model

A simplified mathematical description of a real situation.

Use when

Use to estimate, predict or compare decisions.

Key method

State assumptions, calculate outputs and check limitations.

Example

A fuel model may assume constant miles per litre.

Independent variable

The input variable that is changed or chosen.

Use when

Use when deciding what the model depends on.

Key method

Place it on the x-axis for graphs.

Example

Number of months is independent in a savings model.

Dependent variable

The output variable affected by the input.

Use when

Use when interpreting what the model predicts.

Key method

Place it on the y-axis for graphs.

Example

Total cost depends on the number of units used.

Linear model

A model with a constant rate of change.

Use when

Use when the output changes by the same amount each step.

Key method

y = mx + c.

Example

A taxi fare with fixed charge plus cost per mile is linear.

Gradient

The rate of change in a linear model.

Use when

Use to interpret cost per unit, speed or change per step.

Key method

gradient = change in y / change in x.

Example

A gradient of 0.22 means 22p per unit.

Intercept

The output when the input is zero.

Use when

Use to interpret starting values or fixed charges.

Key method

In y = mx + c, c is the intercept.

Example

A 3.50 intercept may be a booking fee.

Quadratic model

A curved model involving a squared term.

Use when

Use when the change itself changes, such as area or projectile-style contexts.

Key method

Use a formula such as y = ax² + bx + c.

Example

A garden area model can be quadratic if both dimensions change.

Exponential model

A model where values multiply by a constant factor.

Use when

Use for repeated percentage growth or decay.

Key method

final value = starting value × factorⁿ.

Example

A car losing 15% per year has decay factor 0.85.

Growth factor

The multiplier for repeated percentage increase.

Use when

Use with exponential growth.

Key method

growth factor = 1 + rate.

Example

4% growth has factor 1.04.

Decay factor

The multiplier for repeated percentage decrease.

Use when

Use with depreciation or reducing quantities.

Key method

decay factor = 1 - rate.

Example

12% decrease has factor 0.88.

Tolerance

The allowed range around a target measurement.

Use when

Use for manufacturing, building and measurement checks.

Key method

lower limit = target - tolerance; upper limit = target + tolerance.

Example

40 mm ± 0.5 mm allows 39.5 mm to 40.5 mm.

Absolute error

The size of an error in original units.

Use when

Use when comparing a measured value with a true or target value.

Key method

absolute error = |measured - actual|.

Example

82.4 cm instead of 82.0 cm gives 0.4 cm error.

Relative/percentage error

Error compared with the size of the value.

Use when

Use when comparing errors across different scales.

Key method

percentage error = absolute error ÷ actual value × 100%.

Example

2 g error on 50 g is 4%.

Checking units

Making sure calculations and answers use sensible units.

Use when

Use before trusting a model output.

Key method

Track units through the calculation and convert where needed.

Example

Minutes must be converted to hours before using mph.

Model assumptions and limitations

The simplifications and weaknesses in a model.

Use when

Use when judging whether a prediction is reliable.

Key method

State what has been assumed and what might affect accuracy.

Example

A travel model may ignore traffic and weather.