SCENARIO 18-4
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 18-4,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?

Question

Quizplus · Accepted Answer

Removing variables from a regression model can lead to a decrease in the coefficient of multiple determination (R^2), as it measures the proportion of the variance in the dependent variable that is predictable from the independent variables. Removing variables may reduce the explanatory power of the model, thus not increasing R^2.

SCENARIO 18-4 You Decide to Predict Gasoline Prices in Different Cities and Cities