Least square regression equation.
A study is being undertaken of companies going public. Of particular interest is the relationship between the size of the offering and the price per share. A sample of ten companies that recently went public revealed:
|
|
Size (Millions)
|
Price Per Share
|
|
|
|
Company
|
X
|
Y
|
X2
|
XY
|
|
1
|
9
|
15.8
|
81
|
142.2
|
|
2
|
94.4
|
11.3
|
8,911.36
|
1,066.72
|
|
3
|
27.3
|
13.2
|
745.29
|
360.36
|
|
4
|
179.2
|
10.1
|
32,112.64
|
1,809.92
|
|
5
|
71.9
|
11.1
|
5,169.61
|
798.09
|
|
6
|
97.9
|
11
|
9,584.41
|
1,076.90
|
|
7
|
93.5
|
10.9
|
8,742.25
|
1,019.15
|
|
8
|
70
|
11.7
|
4,900.00
|
819
|
|
9
|
160.7
|
10.3
|
25,824.49
|
1,655.21
|
|
10
|
96.5
|
11.6
|
9,312.25
|
1,119.40
|
|
Total
|
900.4
|
117
|
105,383.30
|
9,866.95
|
a) Conclude the regression equation (show your work).
b) What does the slope of regression equation tell us?
c) What would you predict the price per share to be if 95 million shares were offered?