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 sixteen homes sold in Newburg Park in the past year. The data are plotted in the scatter plot in Figure 1. Also given is the product of the distance from the beach and the house price for each of the sixteen houses. (These products, written in the column labelled"xy", may aid in calculations.) Distance from the beach, x (in miles) Selling price, y (in thousands of dollars) xy 11.1 232.2 2577.42 8.8 293.5 2582.8 9.2 279.6 2572.32 12.3 276.2 3397.26 5.5 241.5 1328.25 5.3 303.8 1610.14 4.9 271.1 1328.39 13.9 188.6 2621.54 3.2 321.6 1029.12 10.0 212.1 2121 13.2 199.7 2636.04 15.2 259.5 3944.4 11.2 218.7 2449.44 5.3 275.2 1458.56 7.1 212.7 1510.17 16.8 218.0 3662.4 Send data to calculator Selling price (in thousands of dollars) y 150 200 250 300 350 x 5 10 15 20 0 Distance from the beach (in miles) Figure 1 What is the sample correlation coefficient for these data? Carry your intermediate computations to at least four decimal places and round your answer to at least three decimal places. (If necessary, consult a list of formulas.)
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 sixteen homes sold in Newburg Park in the past year. The data are plotted in the
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What is the sample
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