=
2. Show that
=
∑
(
̅ )(
(
̅)
− (1 −
)
using the method of ordinary least squares. (20 points)
)
= 1 − (1 −
. Start with
)
. (20 points)
3. Solve for the missing values (a.- k.) (11 points)
Source
SS
Model
Residual
2450.41532
a.
Total
8477.76093
f.
R-squared
g.
R-squared adjusted
y
Coef.
x1
df
-1.057388
x2
_cons
MS
2
1563
b.
e.
Std. Error
0.4704453
h.
1.50E-07
12.01966
i.
c.
d.
t
P>|t|
j.
[95% Confidence Interval]
0.025
25.21
5.52
0
0
k.
3.49E-06
7.749835
4.08E-06
16.28949
4. You are employed in a car dealership and you believe that the number of sales personnel on duty
(sales_per) has a significant impact on the number of cars sold (num_cars). The dataset is assumed to be in the file name Problem4.csv. It is assumed to be located in the working directory
C:\Users\LBYACC2\Problem4.
REQUIREMENT: Provide ALL STATA commands necessary to input the data and to create the regression model as well as all necessary tests of robustness for the model. Be sure to store the results in a log file with the following file name “Name_Quiz3_Problem4.”
5. Use the following data to develop a multiple regression model to predict y from x1 and x2. y x1 x2 Year
198
29
1.64
1
214
71
2.81
2
211
54
2.22
3
219
73
2.70
4
184
67
1.57
5
167
32
1.63
6
201
47
1.99
7
204
43
2.14
8
190
60
2.04
9
222
32
2.93
10
197
34
2.15
11
The dataset is assumed to be in the file name Problem5.csv. . It is assumed to be located in the working directory C:\Users\LBYACC2\Problem5.
REQUIREMENT: Provide ALL STATA commands necessary to input the data and to create the regression model as well as all necessary tests of robustness for the model. Be sure to store the results in a log file with the following file name “Name_Quiz3_Problem5.”