Quantitative forecasting can be applied when two conditions are satisfied:
- numerical information about the past is available;
- it is reasonable to assume that some aspects of the past patterns will continue into the future.
There is a wide range of quantitative forecasting methods, often developed within specific disciplines for specific purposes. Each method has its own properties, accuracies, and costs that must be considered when choosing a specific method.
Most quantitative prediction problems use either time series data (collected at regular intervals over time) or cross-sectional data (collected at a single point in time).