Prediction in statistical learning
A prediction problem in statistical learning occurs when there are a significant number of observations and their corresponding outcomes, and the goal is to predict outcomes for a new set of observations where they are unavailable. Let be the set of all input variables and be the set of corresponding outcomes. If is the estimate of the function that maps to , and is the resulting prediction of , assuming the error term averages to zero (), the following holds:
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Prediction in statistical learning
10 themes for Superforecasting
A city's transportation department is considering adding a new bus line. Two planners present their forecasts for its potential ridership:
- Planner A: "My cousin started taking the bus last year and loves it. People are tired of driving. I predict this new line will be immediately popular and serve 5,000 riders per day within the first month."
- Planner B: "Surveys on the proposed route show high interest from 20% of residents. Similar lines in three comparable cities saw a 5-8% ridership increase in their first year. I predict the new line will serve 1,500-2,000 riders per day after six months of operation."
Based on the principles of making a sound forecast, which planner's prediction is more robust and why?
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Match each statement to the category that best describes it. To do this, you must analyze whether the statement is about the future, if it is based on evidence, and if it can be objectively verified.
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Prediction in statistical learning