This document contains a table of 15 data points measuring x, y, x^2, y^2, and xy values. It then performs linear regression analysis to find the line of best fit between x and y. The linear regression equation is y = 0.004x + 19.82 with an R^2 value of 0.029, indicating a weak correlation between x and y.

1. x y x2 y2 xy
1 1521.2 27.1 2314049.44 734.41 41224.52
2 1550.5 29 2404050.25 841 44964.5
3 1568.2 27.2 2459251.24 739.84 42655.04
4 1579.3 26 2494188.49 676 41061.8
5 1606.7 26.2 2581484.89 686.44 42095.54
6 1610.3 26.4 2593066.09 696.96 42511.92
7 1627.2 25.1 2647779.84 630.01 40842.72
8 1645 24.9 2706025 620.01 40960.5
9 1655.7 26.2 2741342.49 686.44 43379.34
10 1682.3 24.5 2830133.29 600.25 41216.35
11 1701.5 25.5 2895102.25 650.25 43388.25
12 1733.8 26.9 3006062.44 723.61 46639.22
13 1741.5 28.3 3032822.25 800.89 49284.45
14 1748.5 31.3 3057252.25 979.69 54728.05
15 1791.3 30.6 3208755.69 936.36 54813.78
∑ 24763 405.2 40971365.9 11002.16 669765.98

2. 32
scx= 90954.6333 30 y = 0.004x + 19.82
R² = 0.029
scy= 56.3573333 28
scxy= 834.806667
26 Series1
r= 0.36872134 Linear (Series1)
24
r2 0.13595543
22
20
1500 1600 1700 1800
0.00917827
a1 5
11.8612245
a0 4
a1 a0
n.xy 10046489.7 = 12522.1 sx 2 . Sy 16601597462.68 = 16182499.94
x.y 10033967.6 x. sxy 16585414962.74
n.x2 614570489 = 1364319.5 n . Sx 2 614570488.5 = 1364319.5
(sx)2 613206169 (sx)2 613206169