TABLE 14-9
You decide to predict gasoline prices in different cities and towns in the United States for your term project. Your dependent variable is price of gasoline per gallon and your explanatory variables are per capita income, the number of firms that manufacture automobile parts in and around the city, the number of new business starts in the last year, population density of the city, percentage of local taxes on gasoline, and the number of people using public transportation. You collected data of 32 cities and obtained a regression sum of squares SSR = 122.8821. Your computed value of standard error of the estimate is 1.9549.
-Referring to Table 14-9, the value of adjusted r² is
A) 0.4576.
B) 0.5626.
C) 0.6472.
D) 95.5414.

Question

Quizplus · Accepted Answer

The adjusted r² is calculated as 1 - (SSR/SST) * (n-1)/(n-k-1), where SSR is the regression sum of squares, SST is the total sum of squares, n is the sample size, and k is the number of explanatory variables. In this case, SSR = 122.8821, SST is not given, n = 32, and k = 6. Plugging these values into the formula, we get adjusted r² = 1 - (122.8821/SST) * (32-1)/(32-6-1) = 0.4576.

TABLE 14-9 You Decide to Predict Gasoline Prices in Different Cities and Cities