Solution:
|
X
|
Y
|
X^2
|
Y^2
|
XY
|
|
30
|
32.2
|
900
|
1036.84
|
966
|
|
20
|
56
|
400
|
3136
|
1120
|
|
20
|
46.2
|
400
|
2134.44
|
924
|
|
45
|
19.5
|
2025
|
380.25
|
877.5
|
|
40
|
23.6
|
1600
|
556.96
|
944
|
|
45
|
16.7
|
2025
|
278.89
|
751.5
|
|
25
|
42.2
|
625
|
1780.84
|
1055
|
|
55
|
13.2
|
3025
|
174.24
|
726
|
|
17.5
|
65.4
|
306.25
|
4277.16
|
1144.5
|
|
35
|
28
|
1225
|
784
|
980
|
|
27.5
|
49.9
|
756.25
|
2490.01
|
1372.25
|
|
27.5
|
35.1
|
756.25
|
1232.01
|
965.25
|
|
30
|
31.2
|
900
|
973.44
|
936
|
|
25
|
29.5
|
625
|
870.25
|
737.5
|
|
40
|
25.6
|
1600
|
655.36
|
1024
|
|
22.5
|
43.4
|
506.25
|
1883.56
|
976.5
|
|
35
|
28.9
|
1225
|
835.21
|
1011.5
|
|
27.5
|
35
|
756.25
|
1225
|
962.5
|
|
22.5
|
38.8
|
506.25
|
1505.44
|
873
|
|
45
|
17.2
|
2025
|
295.84
|
774
|
|
|
|
|
|
|
|
635
|
677.6
|
22187.5
|
26505.74
|
19121
|
Regression equation can be calculated as
Y = a + bx
Here a is Y intercept and b is slope of regression line
Slope of line can be calculated as = (n*Summation(XY) -
Summation(X)*Summation(Y)/ n*Summation(X^2) -
(Summation(X))^2)
= (20*19121 - 635*677.6)/(20*22187.5-635*635) = -1.1809
Intercept can be calculated as
Intercept = Summation(Y) - b*Summation(X)/n = 677.6 -
635*(-1.18)/20 = 71.3736
So regression line is
Y = 71.3736 - 1.1809*X
