We have addressed important astrophysical issues of the large scale structure of the universe with the help of analytical and numerical tools. In particular, we have concentrated on obtaining a better understanding of the environmental dependence of clustering of dark matter and galaxies. We will discuss the development of the analytical framework, the generation of mock catalogs of data, and present results from numerical studies of the comparison of the theory with the simulated data samples and subsequently with actual observational data. <P />The N-body simulations from the Virgo consortium and SDSS data were used to study the clustering properties of dense and less dense subsamples with the help of the correlation function. The dense sample shows a correlation function that is about a factor of ten times or more higher than the less dense sample at large scales. This discernible difference holds true for mock galaxies, dark matter, and data from the Sloan Digital Sky Survey. By utilizing the halo model and adapting the formalism to different environments, we present the correspondence between theoretical models and simulated samples and real data. <P />The very good agreement between the model and results from simulations and data provides strong support for the hierarchical clustering models. This suggests that unless care is taken to study galaxies at fixed halo mass, observed correlations between gastrophysical effects and environment are dominated by the fact that these effects also correlate with the halo mass, and halo mass correlates with environment.