Prediction Intervals

Prediction intervals are a statistical tool used to estimate the range within which future observations are likely to fall, given a set of observed data. Unlike confidence intervals, which estimate the population parameter, prediction intervals take into account both the uncertainty in estimating the population parameter and the variability of future observations. They provide valuable insights into the potential range of outcomes and are widely used in fields such as finance, engineering, and environmental science to make informed decisions based on probabilistic forecasts.

Questions
  • Where will a prediction interval or a confidence interval be narrower: near the mean or further from the mean?
  • A linear regression equation for a data set has a correlation coefficient of r=0.4. Would you be confident using your equation to predict what will happen outside of the data set?