Linear Regression of Ordinary Time Series Data
- As with any other type of bivariate data, it is often useful to apply linear regression to time series data in order to predict values for which we have no data.
- For time series data, time is always the explanatory variable.
- Unprocessed data with seasonality is generally poorly modelled by a linear fit.
Note: if you cannot remember how to construct and interpret a linear fit, revise notes for 3.1 Least Squares Linear Regression and 3.2 Modelling Linear Associations.
Read More »4.5 Analysis of De-seasonalised Data