The territory, considered as a physical environment, is the place where social activities take place in the broadest sense of the term. Health and education structures, services to citizens, industrial production are subordinate to and condition the territory that hosts them. The position of the territories and the resources at their disposal have always, and still today, contribute to determining development opportunities. On the other hand, areas with scarce availability of resources produce depressive effects, such as, for example, the abandonment of inland and mountain areas. The quality of life is influenced by multiple measurable characteristics, to be compared with statistical methods. For example, large urban centers, with respect to rural areas, show greater attractions and services, but require extended times for moving and for the acquisition of services, for carrying out social relations. Furthermore, urban areas have a lower quality of environmental resources, higher crime and major costs. Among the many factors that influence development, the environment plays a predominant role. In fact, in recent years, has grown the civic sensitivity for environmental protection and indicators for its conservation are being monitored more and more frequently. Air pollution, improvement of water treatment, waste disposal, global warming, and extreme events led the administrative authorities to issue increasingly restrictive measures, in order to preserve the territory and the general quality of life. In this context, it is essential to have a quantitative monitoring tool in order to keep the actions and policies adopted under control, assess trends, identify major risk factors and carry out mapping of homogeneous areas. In a nutshell, the statistical method plays an essential role in all its available theoretical articulations. The design of surveys and the adoption of statistical sampling methods allow you to obtain statistical information that meets strict quality principles (updated, disaggregated, relevant and reliable data). The adoption of more or less sophisticated statistical models, on the other hand, makes it possible to effectively and concisely represent complex situations, make comparisons and evaluate the evolution of social, economic and environmental phenomena over time and space.