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
G(-3) = -3-7 = -10;
f(g(-3))=f(-10) = 2 x (-10) + 5 = - 20 + 5 = -15.
<span>associative property of addition and answer is
</span><span>(u + 7) + 13 = u + (7 + 13)</span>
There is no picture so i am not sure what to tell u
