Reference no: EM131226190
The accountant at Rick Wing Coal? Distributors, Inc., in San Francisco 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:
Observation 1 2 3 4 5
Coal Sales y (in millions of tons) 4 1 4 6 5
Weather Index x 2 1 4 5 3
The least squares regression equation that shows the best relationship between coal sales and weather index is ?(round your responses to one decimal? place):
Modifying Above
y with carety=_+_x
where
Modifying Above y with carety ?= Coal Sales and x? = Weather Index.
The coefficient of correlation of the? data,
?r =
?(round your response to three decimal? places).
The standard error of the estimate equals=
?(round your response to two decimal? places).
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