The accountant at Bintong Chen Coal Distributors, Inc., in Newark, Delaware, notes that the demand for coal seems to be tied to an index of weather severity developed by the U.S. Weather Bureau. When weather was extremely cold in the U.S. over the past 5 years (and the index was thus high), coal sales were high. The accountant proposes that one good forecast of next year's coal demand could be made by developing a regression equation and then consulting the Farmer's Almanac to see how severe next year's winter would be. The data for coal sales are shown below: Coal Sales (in millions of tons), y 7 1 7 10 8 Weather Index, x 4 1 5 7 5 The least-squares regression equation that shows the best relationship between coal sales and weather index is (enter your response for the y-axis intercept rounded to two decimal places and for the slope rounded to three decimal places): y= 0 + 1.5x, where y=Coal Sales and x = Weather Index. The coefficient of correlation of the data, r = 0.978 (enter your response rounded to three decimal places). The standard error of the estimate, Sy,x (enter your response rounded to two decimal places).