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In experimental particle physics, we use for data analysis a set of samples to simulate the background and the signal we want to observe. When reading articles, I often encounter a section dedicated to background estimation using the recorded data and not the monte carlo simulated samples.

What is the purpose for that ?

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If data is used to gauge the background levels, it means that the particular quantum mechanical models used in the simulation events are unnecessary in order to extract a significant signal. It does not depend on dynamical assumptions that exist in the generators of the monte carlo events, which vary in how well they desribe data.

For example in this "Search for the Standard Model Higgs boson"

Most background shapes are taken from simulation and normalised using control regions in data except for multijet, which is estimated entirely from data,

It implies that the multijet simulation is not well fitted, so where jets are important in the analysis, data of multijets are used to estimate the background.

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    $\begingroup$ It also serves as yet another way to validate the simulation; or to help you identify where the simulation is deficient. For the main simulations (both the programs and the frameworks on which they are built) this is of great value because the code has a long lifetime and improvements will drive better results in the future. That aspect of refining the tools is something that I overlooked when I first started out, but ended up spending a lot of time on. $\endgroup$
    – dmckee --- ex-moderator kitten
    Commented Jul 18, 2017 at 15:00

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