The following data on sale price, size, and land-to-building ratio for 10 large industrial properties appeared in a paper.
Property | Sale Price (millions of dollars) |
Size (thousands of sq. ft.) |
Land-to- Building Ratio |
1 | 10.5 | 2166 | 1.9 |
2 | 2.5 | 752 | 3.6 |
3 | 30.4 | 2422 | 3.7 |
4 | 1.7 | 223 | 4.8 |
5 | 20.0 | 3917 | 1.6 |
6 | 8.1 | 2867 | 2.3 |
7 | 10.1 | 1698 | 3.1 |
8 | 6.7 | 1046 | 4.7 |
9 | 5.8 | 1109 | 7.5 |
10 | 4.6 | 405 | 17.1 |
(a) Calculate the value of the correlation coefficient between
sale price and size. (Give the answer to three decimal
places.)
r =
(b) Calculate the value of the correlation coefficient between sale
price and land-to-building ratio. (Give the answer to three decimal
places.)
r =
(c) If you wanted to predict sale price and you could use either
size or land-to-building ratio as the basis for making predictions,
which would you use?
Size
Land-to-building ratio
(d) Based on your choice in Part (c), find the equation of the
least-squares regression line you would use for predicting
y = sale price. (Give answers to three decimal
places.)
= ... + ... x
a)
from excel: correl function:
r=correl(sale array, size array) =0.702
b)
r=correl(sale array, land to building array) =-0.329
c)
since absolute value of correlation is higher for size
one should use size
d)
y=718.665+93.808x
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