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TABLE 14-14
An econometrician is interested in evaluating the relation of demand for building materials to mortgage rates in Los Angeles and San Francisco. He believes that the appropriate model is
Y = 10 + 5X1 + 8X2
where X1 = mortgage rate in %
X2 = 1 if SF, 0 if LA
Y = demand in $100 per capita
-Referring to Table 14-14, the fitted model for predicting demand in San Francisco is .
SSR
In statistics, SSR stands for Sum of Squares due to Regression, which measures the variation explained by the regression line.
SSE
A metric indicating the variance between an estimated model's predictions and the actual data, calculated as the sum of squares of errors.
Estimated Regression Equation
A mathematical representation derived from regression analysis that estimates the relationship between variables.
Demand
The quantity of a good or service that consumers are willing and able to purchase at various prices during a specified period of time.
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