Time series
Time series is the definition of the representation of values that are plotted to represent statistics over time. It is in the form of indexed data points, which is in for components that are represented by the data. First, there is a trend; which describes variations in a predictable and reasonable manner over time that can be analyzed to make conclusions. The trend is characterized by a long-term, smooth, and general tendency displayed by the data (Kourentzes et al., 2014). Furthermore, there is a component of the cycle, which is characterized by cyclical variations that correspond with the volatility of business activity. There can also be peculiar cycles that are independent of external effects on a business (Keller & Wittfeld, 2004). The third component is seasonal, whereby the variables repeat in frequency over a definite day, month, or range of months. The specificity of the regular intervals is the underlying characteristic of the seasonal component. Lastly, there is an irregular component, where the variables occur randomly in an uncharacterized manner. There is no seasonality of predictability associated with the irregular component in this case.
An additive model is a statistical model that is used in situations where time series variances remain constant over time. When the time series variables remain unchanged over the use of the time series, then the additive model is used (Chu & Glymour, 2008). On the other hand, there is the multiplicative model. It is used when there is a high variance in the time series variables. When there are changes in the data that are being used in a model, then the most appropriate model to use is the multiplicative model Edmans et al., 2009). There are various ways that can be applied in the projection and showing data in time series. One of the most common ways is regression analysis. That is whereby the relationship between variables is studied over time. There is the projection of the trend using a linear model, which helps in understanding the trend by studying the characteristics of the linear representation of the equation. One of the applications is showing the relationship between economic variables in a country over time. That helps in ascertaining the performance of the economy for better interventions to be applied.