Final answer:
R-squared (R2) in the context of demand estimation for soft drinks measures how well the independent variables explain the variability in demand. A value close to 1 indicates a good model fit, while a value near 0 indicates a poor fit.
Step-by-step explanation:
The R2, or coefficient of determination, is a statistical measure that represents the proportion of the variance for a dependent variable that's explained by an independent variable or variables in a regression model. For the estimated demand for a soft drink, R2 would help us understand how well our independent variables (like price, income, advertising spending, etc.) predict the quantity of soft drinks demanded. An R2 value close to 1 suggests that a large proportion of the variance in the demand for soft drinks is explained by the model, indicating a good fit, whereas an R2 value near 0 indicates a poor fit.