Final answer:
Time series forecasts use past data to predict future outcomes. This method is applied in various fields, such as economics for stock market predictions, streaming services for understanding viewing preferences, and geography for analyzing spatial trends.
Step-by-step explanation:
Forecasts that utilize a series of past data points to make a forecast are known as time series forecasts. This method involves collecting and analyzing historical data to identify patterns, trends, and cycles, which are then projected into the future to predict what will happen next.
In the case of an economist trying to predict stock market outcomes, they would be using time series analysis to compare their predictions with actual market performance, and continually adjusting the model based on the newly accumulated data points.
Companies also employ time series analysis to study user behavior; for example, a streaming service might analyze viewing habits to forecast future viewing patterns. Geographers use this method to assess whether the variables in their analysis accurately predict trends across different locations.
In essence, time series forecasting is a staple in various fields where predicting future trends based on past data is essential.