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# A survey conducted by a research team was to investigate how the education level, tenure in current employment,

and age are related to annual income. A sample of 20 employees is selected and the data are given below.

Education (No. of years) Length of tenure in current employment (No. of years) Age (No. of years) Annual income(\$)

17 8 40 124,000

12 12 41 30,000

20 9 44 193,000

14 4 42 88,000

12 1 19 27,000

14 9 28 43,000

12 8 43 96,000

18 10 37 110,000

16 12 36 88,000

11 7 39 36,000

16 14 36 81,000

12 4 22 38,000

16 17 45 140,000

13 7 42 11,000

11 6 18 21,000

20 4 40 151,000

19 7 35 124,000

16 12 38 48,000

12 2 19 26,000

10 6 44 124,000

Is this correct regression↓? If not, please tell me collect regression.

Also, please tell me how to solve following question.

a.     Check if the F test leads to conclude that an overall regression relationship exists. If yes, use the t test to determine the significance of each independent variable.

b.     What is the conclusion for each test at the 0.05 level of significance?

c.     Remove all independent variables that are not significant at the 0.05 level of significance from the estimated regression equation.

d.     What is your estimated regression equation in this case?

D
E
F
G
H
K
M
(S)
SUMMARY OUTPUT
124,000
30,000
Regression Statistics
193,000
Multiple R
0.818606797
88,000
R Square
0.670117089
27,000
0.608264043
43,000
Standard Error
32446.87447
96,000
Observations
20
110,000
88,000
ANOVA
36,000
df
SS
VS
Significance F
81,000
Regression
3 34218155395 11406051798 10.83401924
0.000393507
38,000
Residual
16
16844794605
1052799663
140,000
Tota
5106295000
11,000
21,000
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%
151,000
Intercept
143481.1924
39925.5954 -3.593714533 0.002431284 -228119.6737 -58842.71115 -228119.6737 -58842.71115
124,000
Education (No. of years)
10011.92124
2570.584809
3.894802928 0.001287795
4562.524882
15461.3176 4562.524882
15461.3176
48,000
Length of tenure in current employment (No. of years)
-2193.883764 2158.829053 -1.016237836 0.324637926 -6770.396912 2382.629385 -
-6770.396912 2382.629385
26,000
Age (No. of years)
2689.240517
986.3534294
2.72644717 0.014939599
598.2646547
4780.216379 598.2646547 4780.216379
124,000
RESIDUAL OUTPUT
25
Predicted
Annual income
Observation
(\$)
Residuals
OUT A W NH
116740.0192
7259.980773
60594.11849
-30594.11849
155338.8613
61.13875
100858.2716
-12858.27159
25563.54852
1436.451478
4 00
52239.48554
-9239.485543
74748.13458
21251.86542
114296.4514
-4296.45139
87195.60087
804.3991346
10
56173.13503
-20173.13503
11
82807.83334
-1807.833338
12
27049.61878
10950.38122
13
100429.3467
39570.6533
14
84264.69906
-73264.69906
15
1892.967947
19107.03205
16
155551.318
-4551.318003
17
125511.5429
-1511.542888
18
92574.0819
-44574.0819
19
23369.66476
2630.335241
20
61801.30014 62198.69986

a. Check if the F test leads to conclude that an overall regression relationship exists. If yes, use the t... View the full answer

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