Suppose a researcher is trying to understand what makes living in a particular city desirable. She uses a list from a popular magazine of the current top 50 desirable cities to live in. Each city was given a desirability score by the magazine's viewers. The researcher is curious about how well she can predict those scores using only two independent variables: the median home price and the number of miles to the closest airport. She obtains the values for median home price and number of miles to the closest airport for each of the 50 cities and calculates the following values: Zero-Order Correlations: Median Home Price and # of Miles to the Closest Airport City Desirability Rating Median Home Price # of Miles to the Closest Airport City Desirability Rating 1.000 0.607 0.400 Median Home Price 1.000 0.065 # of Miles to the Closest Airport 1.000 The researcher computes the partial correlation of 0.455 between the city desirability rating and the number of miles to the closest airport controlling for the median home price. Because this value is not much different from the zero-order correlation between the city desirability rating and the# of miles to the closest airport , the researcher can consider the relationship between these two variables to be , at least with respect to consideration of the median home price. Using the provided correlations and the given partial correlation, the coefficient of multiple determination (R2 ) for the multiple regression equation p