# x27.txt # # Reference: # # S C Narula, J F Wellington, # Linear Regression and the Minimum Sum of Relative Errors, # Technometrics, Volume 19, 1977, pages 185-190. # # Helmut Spaeth, # Mathematical Algorithms for Linear Regression, # Academic Press, 1991, # ISBN 0-12-656460-4. # # Discussion: # # The selling price of houses is to be represented as a function of # other variables. # # There are 28 rows of data. The data includes: # # I, the index; # A0, 1; # A1, the local selling prices, in hundreds of dollars; # A2, the number of bathrooms; # A3, the area of the site in thousands of square feet; # A4, the size of the living space in thousands of square feet; # A5, the number of garages; # A6, the number of rooms; # A7, the number of bedrooms; # A8, the age in years; # A9, 1 = brick, 2 = brick/wood, 3 = aluminum/wood, 4 = wood. # A10, 1 = two story, 2 = split level, 3 = ranch # A11, number of fire places. # B, the selling price. # # We seek a model of the form: # # B = A0 * X0 + A1 * X1 + A2 * X2 + A3 * X3 + A4 * X4 + A5 * X5 # + A6 * X6 + A7 * X7 + A8 * X8 + A9 * X9 + A10 * X10 + A11 * X11 # 14 columns 28 rows Index A0, One A1, the local selling prices, in hundreds of dollars; A2, the number of bathrooms; A3, the area of the site in thousands of square feet; A4, the size of the living space in thousands of square feet; A5, the number of garages; A6, the number of rooms; A7, the number of bedrooms; A8, the age in years; A9, construction type A10, architecture type A11, number of fire places. B, selling price 1 1 4.9176 1.0 3.4720 0.998 1.0 7 4 42 3 1 0 25.9 2 1 5.0208 1.0 3.5310 1.500 2.0 7 4 62 1 1 0 29.5 3 1 4.5429 1.0 2.2750 1.175 1.0 6 3 40 2 1 0 27.9 4 1 4.5573 1.0 4.0500 1.232 1.0 6 3 54 4 1 0 25.9 5 1 5.0597 1.0 4.4550 1.121 1.0 6 3 42 3 1 0 29.9 6 1 3.8910 1.0 4.4550 0.988 1.0 6 3 56 2 1 0 29.9 7 1 5.8980 1.0 5.8500 1.240 1.0 7 3 51 2 1 1 30.9 8 1 5.6039 1.0 9.5200 1.501 0.0 6 3 32 1 1 0 28.9 9 1 16.4202 2.5 9.8000 3.420 2.0 10 5 42 2 1 1 84.9 10 1 14.4598 2.5 12.8000 3.000 2.0 9 5 14 4 1 1 82.9 11 1 5.8282 1.0 6.4350 1.225 2.0 6 3 32 1 1 0 35.9 12 1 5.3003 1.0 4.9883 1.552 1.0 6 3 30 1 2 0 31.5 13 1 6.2712 1.0 5.5200 0.975 1.0 5 2 30 1 2 0 31.0 14 1 5.9592 1.0 6.6660 1.121 2.0 6 3 32 2 1 0 30.9 15 1 5.0500 1.0 5.0000 1.020 0.0 5 2 46 4 1 1 30.0 16 1 5.6039 1.0 9.5200 1.501 0.0 6 3 32 1 1 0 28.9 17 1 8.2464 1.5 5.1500 1.664 2.0 8 4 50 4 1 0 36.9 18 1 6.6969 1.5 6.9020 1.488 1.5 7 3 22 1 1 1 41.9 19 1 7.7841 1.5 7.1020 1.376 1.0 6 3 17 2 1 0 40.5 20 1 9.0384 1.0 7.8000 1.500 1.5 7 3 23 3 3 0 43.9 21 1 5.9894 1.0 5.5200 1.256 2.0 6 3 40 4 1 1 37.5 22 1 7.5422 1.5 4.0000 1.690 1.0 6 3 22 1 1 0 37.9 23 1 8.7951 1.5 9.8900 1.820 2.0 8 4 50 1 1 1 44.5 24 1 6.0931 1.5 6.7265 1.652 1.0 6 3 44 4 1 0 37.9 25 1 8.3607 1.5 9.1500 1.777 2.0 8 4 48 1 1 1 38.9 26 1 8.1400 1.0 8.0000 1.504 2.0 7 3 3 1 3 0 36.9 27 1 9.1416 1.5 7.3262 1.831 1.5 8 4 31 4 1 0 45.8 28 1 12.0000 1.5 5.0000 1.200 2.0 6 3 30 3 1 1 41.0