Arranging magnetic nanoparticles (MNPs) into highly ordered structures, so-called superlattices or mesocrystals, is of great interest from a fundamental point of view, as the employment of the corresponding coupled nanoentities introduces additional degrees of freedom to manipulate the overall magnetic characteristics of such hierarchical materials. Characterizing the associated magnetic interactions on the mesoscopic scale is indispensable for obtaining a profound understanding of the relative strengths of the types of interactions involved, such as dipole-dipole interactions, which affect the collective response of a corresponding mesocrystal. In this paper, nanoparticles are deposited onto silicon substrates by spin coating, leading to two-dimensional monolayered structures showing a close-packed hexagonal arrangement. The MNPs consist of iron oxide (magnetite ${\mathrm{Fe}}_{3}{\mathrm{O}}_{4}$) and are coated with a nonmagnetic polymer (polystyrene). The MNPs are synthesized such that their diameters ${d}_{\text{MNP}}$ are tuned in a range between 9 and 18 nm. A precise manipulation of the shell thickness ${d}_{\text{shell}}$ is achieved by coating the MNPs with polystyrene of different molecular weights. In this fashion, the spacing between the MNPs, ${d}_{\text{spacer}}=2{d}_{\text{shell}}$, is varied in a range between 6 and 14 nm. Within the investigated ${d}_{\text{spacer}}$ range, dipolar interactions govern the collective properties showing distinct distance-dependent characteristics. As ${d}_{\text{spacer}}$ increases, the dipolar coupling strength between the MNPs decreases, as deduced from the spectral features of ferromagnetic resonance experiments. These observations are further corroborated by numerical simulations of the dynamic properties of appropriate model systems. A comparison of the experimental and theoretical findings shows that material parameters, such as the magnetization ${M}_{\text{MNP}}$ and the magnetocrystalline anisotropy ${C}_{\text{MNP}}$ of the MNPs, are reduced compared to their bulk values.