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Elza [17]
3 years ago
13

Suppose the manager of a gas station monitors how many bags of ice he sells daily along with recording the highest temperature e

ach 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 Yˆ = −114.05+2.17X. On one of the observed days, the temperature was 82 °F and 66 bags of ice were sold.
1. Determine the number of bags of ice predicted to be sold by the LSR line, Yˆ, when the temperature is 82 °F.
2. Compute the residual at this temperature.
Mathematics
1 answer:
Maslowich3 years ago
4 0

Answer:

Kindly check explanation

Step-by-step explanation:

Given the following :

Equation of regression line :

Yˆ = −114.05+2.17X

X = Temperature in degrees Fahrenheit (°F)

Y = Number of bags of ice sold

On one of the observed days, the temperature was 82 °F and 66 bags of ice were sold.

X = 82°F ; Y = 66 bags of ice sold

1. Determine the number of bags of ice predicted to be sold by the LSR line, Yˆ, when the temperature is 82 °F.

X = 82°F

Yˆ = −114.05+2.17(82)

Y = - 114.05 + 177.94

Y = 63.89

Y = 64 bags

2. Compute the residual at this temperature.

Residual = Actual value - predicted value

Residual = 66 - 64 = 2 bags of ice

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