Statistical ecology is the area of statistics that deals with the development of new methodology and techniques for analysing ecologidal data. Advanced statistical models and techniques are often needed to provide robust statistical analyses of the available data. The statistical models that are developed can often be separated into two distinct processes: a system process that describes the underlying biological system coupled with an observation process. The system process is often a function of the demographic parameters of interest, such as survival probabilities, transition rates between states and/or abundance; while the observation process describes the data collection process, with the associated observation model parameters conditional on the underlying state of the system. This paper focuses on a number of common forms of ecological data and discusses the associated models and model-fitting approaches, including the incorporation of heterogeneity within the given biological system and integration of different data sources.