Infiltration and inflows (I/I) into either sanitary or stormwater sewer systems are an inevitable issue that must be considered at multiple stages, and from various aspects. Among many factors causing I/I, Rainfall-Derived/Dependent Infiltration and Inflow (RDII) is the most prominent contributor and has mostly been characterized as a percentage, rather than quantified pertinent to particular locations. Although there exist methods for design engineers to evaluate the potential RDII quantities, the available methods have primarily focused on estimation of general amounts, procedures which generally lack sound statistical bases. Better estimates of the RDII amount and improved understanding of the relationship between precipitation and I/I requires more solid quantitative analysis. This paper uses data from the City of London, Ontario, Canada as a case study to present some simple but appropriate statistical approaches to evaluate RDII amounts and explore other deeper relationships. Conventionally, the characteristic of RDII have been modelled in Stormwater Management (SWM) Models based primarily on assumptions. This research uses statistical analysis and inferences to translate data collected in the field into a form can be used in Stormwater Management (SWM) Models, which possess more advantages than just based on assumptions. Further, as the City of London has recently undergone a weeping tile disconnection project, this research also illustrates the benefits of such efforts, both statistically and visually, via SWM model. The results provide informative knowledge for engineers to characterize RDII in a local sewer system.