Probabilistic forecasts primarily belong to the fields of Artificial Intelligence, Big Data and Smart Data, and Digital Transformation. They play a role wherever predictions are made based on large amounts of data \u2013 for example, in weather forecasting, stock prices, or detecting online fraud attempts.<\/p>\n
A probabilistic forecast does not predict a single fixed outcome, but rather considers different possibilities and their probabilities. So, you don't get the answer \u201eIt will rain tomorrow,\u201c but rather \u201eThere is a 70 percent probability that it will rain tomorrow.\u201c.<\/p>\n
Imagine you are using an app that tells you the likelihood of a traffic jam on your route. Instead of \u201eThere is a traffic jam,\u201c the app displays: \u201eThe probability of a traffic jam is 30 percent.\u201c You can then decide for yourself whether to take the route or perhaps reroute.<\/p>\n
Probabilistic forecasts help companies and private individuals to better assess risks and make more informed decisions. They make predictions more transparent and realistic because they include uncertainties, which are always present in real life.<\/p>","protected":false},"excerpt":{"rendered":"