School

California State University, East Bay **We aren't endorsed by this school

Course

STAT MISC

Subject

Statistics

Date

Sep 25, 2023

Type

Other

Pages

27

Uploaded by CoachMole1026 on coursehero.com

Student
GPA
Experience
Salary
1
2.92
3
73,590
2
3.84
9
87,000
If the multiple regression equatio
3
3.04
6
76,970
4
3.20
6
79,320
Explain: Remove the p-value with result high
5
3.61
7
79,530
Remove the variable
from the model and ev
6
2.99
5
71,040
Delete the variables not significicantly affect
7
3.78
8
82,050
8
3.20
5
78,890
9
3.42
7
82,170
10
3.05
5
76,120
SUMMARY OUTPUT
11
3.12
4
77,500
12
3.56
7
83,920
Regression Statistics
13
3.01
5
71,800
Multiple R
0.838484
14
3.15
6
77,000
R Square
0.703056
15
3.05
7
79,000
Adjusted R
0.687005
16
3.24
5
77,800
Standard E
2220.671
17
3.25
6
80,600
Observatio
40
18
3.78
9
87,000
19
3.12
4
78,450
ANOVA
20
3.24
8
80,600
df
SS
MS
21
2.98
5
74,900
Regression
2 4.32E+08 2.16E+08
22
3.24
6
79,200
Residual
37 1.82E+08
4931380
23
3.08
4
77,000
Total
39 6.14E+08
24
3.00
6
77,900
25
2.95
4
76,950
Coefficients
tandard Erro
t Stat
26
3.01
5
76,800
Intercept
53295.45
4566.511
11.67093
27
3.23
7
79,300
GPA
5539.797
1696.536
3.265358
28
3.01
2
72,120
Experience 1257.259
282.8412
4.445103
29
3.45
7
83,900
30
3.85
8
85,200
31
3.00
5
77,300
At this point, Significant F is smaller than 0, w
32
3.23
6
83,500
when we remove unnecessary variable is sc
33
3.80
7
77,000
This is tell us that all of variables are significa
34
3.08
5
75,000
35
3.15
7
79,200
Improve multiple regression equa
36
3.35
7
80,400
y = (1257.259*Experience) +(553
37
3.09
7
80,200
for example: student 36 with GPA
38
3.35
9
84,800
y = (1257.259 * 7) + (5539.797* 3
39
3.16
3
72,800
40
2.76
7
75,000

on in the previous question is not "good for use", how would you suggest impr
her than 0.05 because not contribute in significance in explaining the data given, which is school ranking d
valuate adjusted R squareto see how much impact in new model
to the data
F
ignificance F
43.8013075182 1.756E-10
P-value
Lower 95%Upper 95%Lower 99.0%
Upper 99.0%
5.7837517E-14
44042.82
62548.08
40895.5
65695.39
0.00235962571
2102.289
8977.304
933.009
10146.58
7.7134804E-05
684.1677
1830.349
489.229
2025.288
which is good. R square is 70.30%, and adjusted r square is smaller than r square is 68.7% which are als
chool ranking, all of the p-value of GPA and Experience are
very small and close to 0, smaller than 0.05.
ant, good fit data.
ation and numeric example
39.797 *GPA) +53295.45
A is 3.35 and experience is 7
3.35) + 53295.45
=
80654.58

roving this multiple regression equation? Present the improved multiple regression
due to the p-value higher than 0.05 for question 4 answer
so good fit.