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We want to predict the selling price of a house in Newburg Park, Florida, based on the distance the house lies from the beach. Suppose

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We want to predict the selling price of a house in Newburg Park, Florida, based on the distance the house lies from the beach. Suppose that we're given the data in the table below. These data detail the distance from the beach (x, in miles) and the selling price (y, in thousands of dollars) for each of a sample of fifteen homes sold in Newburg Park in the past year. The data are plotted in the scatter plot in Figure 1. Distance from the Selling price, y beach, x (in thousands of (in miles) dollars 7.7 283.7 6.7 307.8 7.4 221.9 $50- 6.0 272.2 10.1 273.8 300 - 13.7 200.0 Selling price (in thousands of dollars) 250- 17.3 214.4 13.1 193. 200- 3.8 274.3 150- 11.5 208.7 4.1 313.8 20 10.7 226.5 Distance from the beach (in miles) 13.4 262.3 Figure 1 8.5 229.1 8.4 241.4 Send data to calculator Send data to Excel The least-squares regression line for these data has a slope of approximately -7.03. Answer the following. Carry your intermediate computations to at least four decimal places, and round your answers as specified below. (If necessary, consult a list of formulas.) (a) What is the value of the y-intercept of the least-squares regression line for these data? Round your answer to at least two decimal places. 0 (b) What is the value of the sample correlation coefficient for these data? Round your answer to at least three decimal places. X

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