The formation of the first luminous sources in the Universe, such as the first generation of stars and accreting black holes, led to the ionization of hydrogen gas present in the intergalactic medium (IGM). This period in which the Universe transitioned from a cold and neutral state to a predominantly hot and ionized state is known as the Epoch of Reionization (EoR). The EoR is one of the least understood epochs in the Universe's evolution mostly due to the lack of direct observations. We can probe the reionization process with the  21-cm signal, produced by the spin-flip transition in neutral hydrogen. However, current radio telescopes have not been able to detect this faint signal. The low-frequency component of the Square Kilometre Array (SKA-Low), will be sensitive enough not only to detect the 21-cm signal produced during EoR but also to produce images of its distribution on the sky. A sequence of such 21-cm images from different redshifts will constitute a three-dimensional, tomographic, data set. Before the SKA comes online, it is prudent to develop methods to analyse these tomographic images in a statistical sense. In this thesis, we study the prospect of understanding the EoR using such tomographic analysis methods. In Paper I, II and V, we use simulated 21-cm data sets to investigate methods to extract and interpret information from those images.  We implement a new image segmentation technique, known as superpixels, to identify ionized regions in the images and find that it performs better than previously proposed methods. Once we have identified the ionized regions (also known as bubbles), we can determine the bubble size distribution (BSD) using various size finding algorithms and use the BSDs as a summary statistics of the 21-cm signal during reionization. We also investigate the impact of different line of sight effects, such as light-cone effect and redshift space distortions on the measured BSDs. During the late stages of reionization, the BSDs become less informative since most of the IGM has become ionized. We therefore propose to study the neutral regions (also known as islands) during these late times. In Paper V, we find that most neutral islands will be relatively easy to detect with SKA-Low as they remain quite large until the end of reionization and their size distribution depends on the properties of the sources of reionization. Previous studies have shown that the 21-cm signal is highly non-Gaussian. Therefore the power spectrum cannot characterize the signal completely. In Paper III and IV, we use the bispectrum, a higher-order statistics related to the three-point correlation function, to characterize the signal. In Paper III, we probe the non-Gaussianity in the 21-cm signal caused by temperature fluctuations due to the presence of X-Ray sources. We find that the evolution of the normalized bispectrum is different from that of the power spectrum, which is useful for breaking the degeneracy between models which use different types of X-Ray sources. We also show that the 21-cm bispectrum can be constructed from observations with SKA-Low. Paper IV presents a fast and simple method to study the so-called squeezed limit version of the bispectrum, which describes how the small-scale fluctuations respond to the large-scale environment. We show that this quantity evolves during reionization and differs between different reionization scenarios.