SCENARIO 17-4
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 Scenario 17-4, the value of adjusted $r ^ { 2 }$ is
A) 0.4576
B) 0.5626
C) 0.6472
D) 95.5414

Question

Quizplus · Accepted Answer

The adjusted $r ^ { 2 }$ is calculated as:$r ^ { 2 } _{adj} = 1 - \frac{(n-1)MSE}{SST}$where:n is the sample sizeMSE is the mean square errorSST is the total sum of squaresIn this case, we have:n = 32MSE = 1.9549^2 = 3.8246SST = 122.8821Plugging these values into the formula, we get:$r ^ { 2 } _{adj} = 1 - \frac{(32-1)3.8246}{122.8821} = 0.4576$Therefore, the correct answer is A) 0.4576.

SCENARIO 17-4 You Decide to Predict Gasoline Prices in Different r2r ^ { 2 }r2

SCENARIO 17-4
You Decide to Predict Gasoline Prices in Different $r ^ { 2 }$