Do heavier cars really use more gasoline? Suppose a car is chosen at random. Let x be the weight of the car (in hundreds of pounds), and let y be the miles per gallon (mpg).
x | 27 | 43 | 31 | 47 | 23 | 40 | 34 | 52 |
y | 30 | 20 | 25 | 13 | 29 | 17 | 21 | 14 |
Complete parts (a) through (d), given Σx = 297, Σy = 169, Σx2 = 11,737, Σy2 = 3861, Σxy = 5845, and r ≈ −0.944.
(a) Verify the given sums Σx, Σy, Σx2, Σy2, Σxy, and the value of the sample correlation coefficient r. (Round your value for r to three decimal places.)
Σx =
Σy =
Σx2 =
Σy2 =
Σxy =
r =
(b) Find x, and y. Then find the equation of the least-squares line ŷ = a + bx. (Round your answers for x and y to two decimal places. Round your answers for a and b to three decimal places.)
x=
y=
ŷ = + x
(c) Find the value of the coefficient of determination r2. What percentage of the variation in y can be explained by the corresponding variation in x and the least-squares line? What percentage is unexplained? (Round your answer for r2 to three decimal places. Round your answers for the percentages to one decimal place.)
r2 =
explained = %
unexplained = %
(d) Suppose a car weighs x = 40 (hundred pounds). What does the least-squares line forecast for y = miles per gallon? (Round your answer to two decimal places.)
= mpg
ΣX = 297
ΣY = 169
ΣX * Y = 5845
ΣX2 = 11737
ΣY2 = 3861
Part a)
r = -0.944
part b)
X̅ = Σ( Xi / n ) = 297/8 = 37.12
Y̅ = Σ( Yi / n ) = 169/8 = 21.12
Equation of regression line is Ŷ = a + bX
b = -0.604
a =( Σ Y - ( b * Σ X) ) / n
a =( 169 - ( -0.6037 * 297 ) ) / 8
a = 43.536
Equation of regression line becomes Ŷ = 43.5358 - 0.6037
X.
part c)
Coefficient of Determination
= 0.891
Explained variation = 0.891* 100 = 89.1%
Unexplained variation = 1 - 0.891* 100 = 10.9%
part d)
When X = 40
Ŷ = 43.536 + -0.604 X
Ŷ = 43.536 + ( -0.604 * 40 )
Ŷ = 19.38
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