In this example we use the typical sales price of homes in a random sample of UScounties (recorded with units as $1000 per square foot) to predict the typical rentalcost in the county (in units of $ per square foot).y: The typical Rental Cost in the county (units: $ per square foot).x: The typical sales price of properties in the county (units: $1000 per square foot).Assume we compare counties A and B. County A has a typical sales price of propertiesat $258 per square foot higher than county B.Assume the regression equation is ŷ = 0.5 +2.2x. This model would predictthe Rental cost in county A to be. $ per square foot higher than the rental costin county B.Record your answer with at least 3 decimal places. You should really carefullyconsider the units for this problem.567.6A calculation to report a predicted change in y for a given change in x shouldnot require using the intercept as part of the calculation. Based on theinterpretation of the slope an additional $1000 increase in the typical salesprice per square foot increases the predicted rental price per square foot by$2.20. Try to consider expanding the interpretation of the slope here.

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In this example we use the typical sales price of homes in a random sample of US counties (recorded with units as $1000 per square foot) to predict the typical rental cost in the county (in units of $ per square foot). y: The typical Rental Cost in the county (units: $ per square foot). x: The typical sales price of properties in the county (units: $1000 per square foot). Assume we compare counties A and B. County A has a typical sales price of properties at $258 per square foot higher than county B. Assume the regression equation is the Rental cost in county A to be in county B. = 0.5 +2.22. This model would predict $ per square foot higher than the rental cost Record your answer with at least 3 decimal places. You should really carefully consider the units for this problem.