correlacion lineal ejemplo 2

1. x y x2 y2 xy
1 821.7 836.70 675190.89 700066.89 687516.39
2 864.8 838.80 747879.04 703585.44 725394.24
3 868.9 828.40 754987.21 686246.56 719796.76
4 907.3 829.20 823193.29 687572.64 752333.16
5 932.7 805.50 869929.29 648830.25 751289.85
6 973.2 787.80 947118.24 620628.84 766686.96
7 978.4 782.00 957266.56 611524 765108.8
8 984 757.60 968256 573957.76 745478.4
9 1016.4 761.20 1033068.96 579425.44 773683.68
10 1050.1 762.50 1102710.01 581406.25 800701.25
11 1082.3 765.60 1171373.29 586143.36 828608.88
12 1083.8 745.90 1174622.44 556366.81 808406.42
13 1121.3 749.00 1257313.69 561001 839853.7
14 1130.4 740.00 1277804.16 547600 836496
15 1136.6 715.90 1291859.56 512512.81 813691.94
∑ 14951.9 11706.1 15052572.6 9156868.05 11615046.4

2. scx= 148618.389 860.00
scy= 21349.5693
- 840.00
scxy= 53516.0093
820.00
-
r= 0.95006405 800.00
r2 0.9026217 Series1
780.00
Linear (Series1)
y = -0.343x + 1124
760.00 R² = 0.891
a1 -0.36009009
1139.34206 740.00
a0 9
720.00
700 800 900 1000 1100 1200
a1 a0
n.xy 174225696 = -802740.14 sx 2 . Sy 176206920464.04 = 2539907747.33
x.y 175028437 x. sxy 173667012716.72
n.x2 225788589 = 2229275.84 n . Sx 2 225788589.5 = 2229275.84
(sx)2 223559314 (sx)2 223559313.6