When no more than 110 units are produced, the cost of producing y units is given by C(x).
1 answer:
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Answer:
a)
Price=150.414-16.626 Age
b)
$34.032
c)
We can't estimate the price of 18 year old car using the above regression equation because the price of 18 year old car falls outside the scope of the model
Step-by-step explanation:
Age(X) Price(Y)
8 18
3 94
6 50
9 21
2 145
5 42
6 36
3 99
a)
The regression equation can be written as
y=a+bx
a=ybar-bxbar
xbar=sumx/n
xbar=(8+3+6+9+2+5+6+3)/8=5.25
ybar=sumy/n
ybar=(18+94+50+21+145+42+36+99)/8=63.125
x y x-xbar y-ybar (x-xbar)^2 (x-xbar)(y-ybar)
8 18 2.75 -45.125 7.5625 -124.09375
3 94 -2.25 30.875 5.0625 -69.46875
6 50 0.75 -13.125 0.5625 -9.84375
9 21 3.75 -42.125 14.0625 -157.96875
2 145 -3.25 81.875 10.5625 -266.09375
5 42 -0.25 -21.125 0.0625 5.28125
6 36 0.75 -27.125 0.5625 -20.34375
3 99 -2.25 35.875 5.0625 -80.71875
Total 43.5 -723.25
b=-723.25/43.5
b=-16.626
a=ybar-bxbar
a=63.125-(16.626)*5.25
a=150.414
Thus, the required regression equation is
y=150.414-16.626 x
Price=150.414-16.626 Age
b)
For predicting price of 7 years old car we put x=7 in the estimated regression equation
y=150.414-16.626 x
y=150.414-16.626(7)
y=150.414-116.382
y=34.032
The predicted price of a 7 year old car is $34.032.
c)
We can't estimate the price of 18 year old car using the above regression equation because the price of 18 year old car falls outside the scope of the model. The estimate of price is only valid for 2 to 9 year old car.