Final answer:
Regression involves a continuous target, utilized in models to predict a variable based on its relationship with other variables. For instance, a change in the regression line's intercept will shift the line up or down while maintaining its parallelism. Economists use such models to forecast market behaviors, like predicting the demand for goods at various prices.
Step-by-step explanation:
Regression involves a continuous target. In the context of regression analysis in mathematics, particularly when dealing with linear regression models, this implies forecasting or estimating a numerical value based on relationship modeling between independent (predictor) variables and a dependent (response) variable which is continuous, such as temperature, prices, or scores. To visualize changes in intercepts graphically, consider that a larger intercept results in the regression line shifting up, while a smaller intercept results in it shifting down, maintaining parallelism with the original line.
Using regression, economists may create and solve models addressing questions such as the impact of economic growth on unemployment rates. These models are essentially systems of equations like the one representing the demand for personal pizzas (Qd = 16-2P). In this equation, Qd represents the quantity demanded at a given price P. By solving the system of equations involving both demand and supply curves, economists can predict equilibrium prices and quantities in the market.