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Linear Regression
Q1)
x
y
1
12
2
7
3
15
4
9
5
12
6
20
7
19
8
20
9
25
10
30
12
40
The gradient of the regression line is:
The y intercept of the regression line is:
The equation of the regression line is:
y =
x +
The model predicts the value of y when x = 5.5 is:
Q2)
x
y
0.1
22
0.4
17
0.7
15
0.6
16
0.9
13
1.4
9
1.5
10
1.9
7
2
5
2.3
6
2.5
4
The gradient of the regression line is:
The y intercept of the regression line is:
The equation of the regression line is:
y =
x +
The model predicts the value of y when x = 0.3 is:
Q3)
x
y
1
70
2
69
3
67
4
66
5
65
6
63
7
62
8
61
9
60
10
58
The gradient of the regression line is:
The y intercept of the regression line is:
The equation of the regression line is:
y =
x +
The model predicts the value of y when x = 20 is:
Q4)
x
y
18
37
36
54
45
63
22
42
69
84
72
91
13
33
33
49
59
79
79
98
10
32
53
71
The gradient of the regression line is:
The y intercept of the regression line is:
The equation of the regression line is:
y =
x +
The model predicts the value of y when x = 40 is:
Q5)
x
y
20
26
23
30
30
45
38
48
39
46
45
60
45
64
48
68
55
70
71
92
The gradient of the regression line is:
The y intercept of the regression line is:
The equation of the regression line is:
y =
x +
The model predicts the value of y when x = 80 is:
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