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

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, if variables that measure the number of new business starts in the last year and population density of the city were removed from the multiple regression model,
Which of the following would be true?

A) The adjusted $r ^ { 2 }$ will definitely increase.
B) The adjusted $r ^ { 2 }$ cannot increase.
C) The coefficient of multiple determination will not increase.
D) The coefficient of multiple determination will definitely increase.