In: Statistics and Probability
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 | 25 | 42 | 33 | 47 | 23 | 40 | 34 | 52 | 
| y | 31 | 22 | 25 | 13 | 29 | 17 | 21 | 14 | 
Complete parts (b) through (e), given Σx = 296, Σy = 172, Σx2 = 11,676, Σy2 = 4006, Σxy = 5924, and
r ≈ −0.932.
(b) 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 = | 
(c) Find x, and y. Then find the equation of the
least-squares line  = 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 | = | |
| = | + x | 
(d) Graph the least-squares line. Be sure to plot the point
(x, y) as a point on the line.
(e) 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 | % | 
(f) Suppose a car weighs x = 42 (hundred pounds). What
does the least-squares line forecast for y = miles per
gallon? (Round your answer to two decimal places.)
mpg

b)
| ΣX = | 296.000 | 
| ΣY= | 172.000 | 
| ΣX2 = | 11676.000 | 
| ΣY2 = | 4006.000 | 
| ΣXY = | 5924.000 | 
| r = | -0.932 | 
c)
| X̅=ΣX/n = | 37.00 | |
| Y̅=ΣY/n = | 21.50 | |
| ŷ = | 43.986+(-0.608)x | 
e)
| coefficient of determination r2 = | 0.868 | |||
| explained = | 86.8% | |||
| unexplained= | 13.2% | |||
f)
| predicted value =43.986+-0.608*42= | 18.45 | ||