Suppose the manager of a gas station monitors how many bags of ice he sells daily along with recording the highest temperature each day during the summer. The data are plotted with temperature, in degrees Fahrenheit (°F), as the explanatory variable and the number of ice bags sold that day as the response variable. The least squares regression (LSR) line for the data is Ý = -151.05 + 2.65X. On one of the observed days, the temperature was 82 °F and 68 bags of ice were sold. Determine the number of bags of ice predicted to be sold by the LSR line, Ý , when the temperature is 82 °F. Enter your answer as a whole number, rounding if necessary. ice bag Using the predicted value you just found, compute the residual at this temperature. residual = ice bag II (>

College Algebra
7th Edition
ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:James Stewart, Lothar Redlin, Saleem Watson
Chapter1: Equations And Graphs
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Suppose the manager of a gas station monitors how many bags of ice he sells daily along with recording the highest temperature each day during the summer. The data are plotted with temperature, in degrees Fahrenheit (°F), as the explanatory variable and the number of ice bags sold that day as the response variable. The least squares regression (LSR) line for the data is ?ˆ=−151.05+2.65?Y^=−151.05+2.65X.

On one of the observed days, the temperature was 82 °F82 °F and 68 bags of ice were sold. Determine the number of bags of ice predicted to be sold by the LSR line, ?ˆY^, when the temperature is 82 °F.82 °F. Enter your answer as a whole number, rounding if necessary.

Suppose the manager of a gas station monitors how many bags of ice he sells daily along with recording the highest
temperature each day during the summer. The data are plotted with temperature, in degrees Fahrenheit (°F), as the
explanatory variable and the number of ice bags sold that day as the response variable. The least squares regression (LSR)
line for the data is Ý = -151.05 + 2.65X.
On one of the observed days, the temperature was 82 °F and 68 bags of ice were sold. Determine the number of bags of ice
predicted to be sold by the LSR line, Ý ,when the temperature is 82 °F. Enter your answer as a whole number, rounding if
necessary.
ice bags
Using the predicted value you just found, compute the residual at this temperature.
residual =
ice bags
Transcribed Image Text:Suppose the manager of a gas station monitors how many bags of ice he sells daily along with recording the highest temperature each day during the summer. The data are plotted with temperature, in degrees Fahrenheit (°F), as the explanatory variable and the number of ice bags sold that day as the response variable. The least squares regression (LSR) line for the data is Ý = -151.05 + 2.65X. On one of the observed days, the temperature was 82 °F and 68 bags of ice were sold. Determine the number of bags of ice predicted to be sold by the LSR line, Ý ,when the temperature is 82 °F. Enter your answer as a whole number, rounding if necessary. ice bags Using the predicted value you just found, compute the residual at this temperature. residual = ice bags
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