TABLE 1215 A business statistics student decides to predict gasoline prices in different cities and towns in the United States for the term project. The dependent variable is price of gasoline per gallon and the 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. Data of 32 cities was collected and a regression sum of squares SSH = 122.3321 was obtained. The computed value of standard error of the estimate is 1.9549. 19. Referring to Table 1216, if variables that measure the number of new business starts in the last year and population density of the city are removed from the multiple regression model, which of the following is true? a. The adjusted IE will definitely increase. b. The adjusted r2 can never increase. c. The coefficient of multiple determination can never increase. d. The coefficient of multiple determination will definitely increase