What is it?
Statistical modelling is the use of mathematical models and statistical concepts to analyze and understand complex data sets, making informed decisions and predictions.
Statistical models
A statistical model is a set of statistical assumptions concerning the generation of the data. The statistical model represents the data-generating process in itself, with added intrinsic random errors that could not be predicted.
For example, if a statistical model tries to predict the generation of data using a function, it needs to assume that there may be some variables that cannot be controlled or let alone be observed. This generate random errors, represented by the letter .
Because of this effect, every model should account for errors. For example, given a function one could express it accounting for errors just by adding the errors as part of the function, .
Models vs Randomness
In most cases, the errors of a statistical model could be simplified to the randomness of the problem, which in itself, it’s impossible to model. One might be able to model how random the problem is, but not the randomness itself.