## 5.2 Time-series models

A time-series is a sequence of evenly spaced events (numerical data observed at regular intervals of time)

Time-series forecasts predict the future based solely of the past values of the variable

Other variables are ignored

Common time-series models are:

- Moving averages
- Exponential smoothing
- Trend projections
- Decomposition

Regression models (simple and multiple) are used in trend projections and one type of decomposition model

Regular time-series are annually, quarterly, daily, hourly data, etc.

Time-series data are usually visualized using two-dimensional line plot

The vertical axis measures the variable of interest, while the horizontal axis corresponds to the time periods