Time series as the most important statistical characteristic of a process or phenomenon

In any scientific sphere and field of knowledge, there are phenomena, the study of which is expedient to produce, taking into account all the changes for a particular time interval. As for the everyday environment of a person, it is of interest for him, for example, how the prices for a particular product have changed over the past year, which is shown by regular examinations in medical clinics, etc.

In statistics, the totality of changes occurring with a particular object for a certain period of time is nothing more than a time series. At any level of this characteristic at any given time, a number of factors affect, each of which can be attributed either to random or to system-forming moments that affect both the short-term trend and cyclical fluctuations.

Analyzing a different combination of these factors, one can come to the conclusion that the time series, depending on one or another sphere, can take one of the following forms. First, a significant part of the economic indicators of both the macro and micro levels is in a constant dynamic change, as they are influenced by a huge number of factors. At the same time, despite the fact that these factors are often directed in different directions, in their totality they form a unidirectional trend, indicating progress or regress in the development of a given indicator.

Secondly, considering the time series for this or that indicator, one can clearly see that it undergoes appreciable cyclic fluctuations. This may be due to the change of seasons, global trends or the duration of the cycle of performance of certain works.

To find out which actual time series possesses a time series, it is necessary to multiply or multiply its random trend and cyclic components in vectorial form. The result obtained as a result of the addition will be an additive model of the time series, and if multiplication is used, the multiplicative model will be presented as a result.

The main task of any statistical research is to determine the quantitative indicators of all three main components of a given time series. This is necessary in order to predict the values of this series that can be expected in the future.

In a number of cases, scientists are required to sample a certain number of observations at roughly equal intervals, that is, to have a stationary time series. It is obtained in those cases when the trend is removed from the dynamic time series, that is, the factors by which short-term trends are formed.

Thus, the time series is the aggregate of the quantitative values of a given indicator taken over a certain time interval. The formation of each level is influenced by many factors that are both short-term and long-term.