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
Answer:
Plug in your variables value.
Step-by-step explanation:
For your case, plug in -6 into the y slot
12(5+2y)= -(6-9y) +4y
12(5+2x-6)= -(6-9x-6)+4y see if that works!
Answer:
a=-4
b=2
c=7
so therefore a*b*c=-4*2*7
