Suppose a housing advocacy group is interested in looking at what affects housing costs, so they collect data for 351 counties in their state and compare the fair market rent for a four-bedroom unit with the following county-level data: population per square mile, per capita income, percent of population speaking language other than English at home (ESL), and percent of population with at least a bachelor’s education. The results of the regression are shown in the following table:

a. Indicate which, if any, of these variables is a significant predictor of housing prices.
b. Solve for the rent for a county with a population density of 550/square mile, $30,000 income per capita, 8% ESL, and 40% with a college degree.
c. Interpret the regression coefficients for population density and college degree.

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Constant Population Density Income per Capita ESL (%) College Degree (%) b SE 301.765 66.260 0.033 0.009 0.054 0.004 0.989 1.975 -15.723 2.600 t 4.554 3.498 13.274 0.501 -6.047 Sig. 0.001 0.001 0.001 0.617 0.001