Dynamic Series

A time series is a series of sequential values ​​of a statistical indicator (mean, mode, median, etc.) changing over time. This series is used for processing materials from biomedical research, as well as in other areas where time series analysis is required.

In medicine, time series can be used to study changes in a patient's health status over time. For example, if a patient is undergoing treatment, changes in his condition, such as blood pressure levels, blood glucose levels, etc., can be monitored. This allows you to evaluate the effectiveness of treatment and adjust it if necessary.

In addition, time series are used in economics to analyze the dynamics of prices for goods and services, demand for various products, etc. In this case, time series analysis makes it possible to determine trends and patterns in changes in economic indicators, which can help in decision-making in the market.

Various statistical methods are used to analyze time series, such as analysis of averages, analysis of variance, correlation analysis, etc. It is also possible to use specialized data processing software packages such as R or Python.

Thus, time series is an important tool for time series analysis and can be used in various fields related to the study of changes over time.

Time series are a series of sequential numerical values ​​of a statistical phenomenon that varies depending on the selected time period. They are widely used in medical statistics to analyze human health data.

When analyzing time series, the statistical technique of time series is used. The dynamics series reflects the dynamics of the development of the phenomenon over the period. Number of observations (