In any scientific field and field of knowledge, there are phenomena, the study of which is advisable to produce, taking into account all the changes over a particular time period. As for the daily environment of a person, here it is of interest to him, for example, how prices for a particular product have changed over the past year, as shown by regular examinations in medical clinics, etc.
In statistics, the totality of changes occurring with one or another object over a certain period of time is nothing but a time series. Any level of this characteristic at one time or another is affected by a number of factors, 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 various combinations of these factors, we can conclude that the time series, depending on a particular area, can take one of the following forms. First of all,a significant part of economic indicators, both macro- and micro-level, is in constant dynamic change, since 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, showing progress or regression in the development of a particular indicator.
Secondly, considering the time series by one or another indicator, one can clearly see that it is subject to noticeable cyclical fluctuations. This may be due to the change of seasons, global trends, or the duration of the cycle of certain jobs.
To find out what actual characteristic a time series has at a particular point in time, it is necessary to vector add or multiply its random trend and cyclic components. The result obtained as a result of addition will be an additive model of the time series, and if multiplication is applied, then the result will be a multiplicative model.
The main task of any statistical study is to determine the quantitative indicators of all three main components of a particular time series. This is necessary in order to predict the values of this series that can expect us in the future.
In a number of cases, scientists need to sample a certain number of observations at approximately equal time intervals, that is, to have a stationary time series. Heis obtained in those cases when the trend is removed from the dynamic time series, that is, the factors with the help of which the formation of short-term trends takes place.
Thus, a time series is a set of quantitative values of one or another indicator, taken over a certain time period. The formation of each level is influenced by many factors, both short-term and long-term.
