# Models

The core of all good research is the creation of *models*. Models explain how things work. Any explanation of how a market works is, by definition, a model. We cannot estimate anything without models. Think about an estimate of new sales for a product. The only way we can create such an estimate is by taking into account the factors that determine how many people will buy. Less obviously, even a simple estimate, such as the proportion of people that are women, can only be obtained by the application of numerous models (we return to this later).

The term 'model' can conjure fear in the minds of the uninitiated. Some people imagine that models are complex sets of equations that can only be understood by statisticians and mathematicians. This is a misunderstanding. The technical meaning of the word 'model' is identical to the understanding you had as a child. Consider a model of Copenhagen’s harbor, built out of Lego. This is a model in exactly the same way that we use the term 'model' on this site: it is something designed to look like the real things, but it is not actually the real thing.

A model is a simplification of reality. Good models of markets capture the key aspects of how markets work. Bad models misrepresent reality.

We can build a model out of wood, Lego, metal, clay and any number of other materials. Models can be expressed in words:

`The amount of advertising determines the level of sales. `

Models can be combinations of images and words:

And as equations:

`$Sales = 121 + 4.1 × $Advertising expenditure`

Each of these examples of models differs in their *precision*. The equation is generally the most precise type of model (although the precision will be misleading if the equation is wrong). Models also differ markedly in terms of their complexity. The models we have seen so far are all simple, involving only a few variables. In real-world applications much more complex models are often required, such as the model shown below, which is discussed in Laddering).