An analytic model is developed to understand how the spatial distribution of dark matter haloes is biased relative to the mass. The model extends the Press-Schechter formalism to determine the statistical distribution of dark haloes in the initial density field, which is assumed Gaussian. Gravitational motions are treated using a spherical collapse approximation. The model is tested against N-body simulations and shows good agreement with the bias function, which relates the overdensity of haloes to the mass overdensity. This bias function is used to calculate the cross-correlation between dark haloes and mass, showing excellent agreement with simulation results. The model also predicts the autocorrelation function of dark haloes, which is proportional to that of the mass over a wide range of scales. This allows for an entirely analytic estimate of the autocorrelation function of dark haloes. The model is used to study how the distribution of galaxies may be biased with respect to the mass. The results suggest that the amplitude of cosmic mass fluctuations and the density of the Universe can be measured using these techniques. The model is tested against simulations and shows good agreement, particularly for large scales. The model also accounts for halo exclusion effects, which significantly reduce the variance in the count of objects within fixed radius spheres. The results show that the autocorrelation function of dark haloes can be accurately predicted using the model, even in the nonlinear regime. The model provides a useful description of the bias function and can be used to understand the clustering of galaxies.An analytic model is developed to understand how the spatial distribution of dark matter haloes is biased relative to the mass. The model extends the Press-Schechter formalism to determine the statistical distribution of dark haloes in the initial density field, which is assumed Gaussian. Gravitational motions are treated using a spherical collapse approximation. The model is tested against N-body simulations and shows good agreement with the bias function, which relates the overdensity of haloes to the mass overdensity. This bias function is used to calculate the cross-correlation between dark haloes and mass, showing excellent agreement with simulation results. The model also predicts the autocorrelation function of dark haloes, which is proportional to that of the mass over a wide range of scales. This allows for an entirely analytic estimate of the autocorrelation function of dark haloes. The model is used to study how the distribution of galaxies may be biased with respect to the mass. The results suggest that the amplitude of cosmic mass fluctuations and the density of the Universe can be measured using these techniques. The model is tested against simulations and shows good agreement, particularly for large scales. The model also accounts for halo exclusion effects, which significantly reduce the variance in the count of objects within fixed radius spheres. The results show that the autocorrelation function of dark haloes can be accurately predicted using the model, even in the nonlinear regime. The model provides a useful description of the bias function and can be used to understand the clustering of galaxies.