Consider the following computer output of a multiple regression analysis relating annual salary to years of education and years of work experience. Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA 0.7352 0.5405 0.5205 2130.9497 49

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
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Chapter4: Equations Of Linear Functions
Section4.6: Regression And Median-fit Lines
Problem 17HP
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^
ol
Consider the following computer output of a multiple regression analysis relating annual salary to years of education and years of work experience.
esc
1
1
A
1
option
wer
Ⓒ2022 Hawkes Learning
Z
☺
@
2
W
S
Coefficients Standard Error t Stat
14281.78907
2352.4989
829.0451
How much would you expect your salary to increase if you had one more year of education?
X
H
command
Intercept
Education (Years)
Experience (Years)
#
3
E
D
df
SS
MS
F
Regression 2 245,665,739.0934 122,832,869.5467 27.0501
Residual 46 208,883,538.9066
Total
4,540,946.4980
48 454,549,278.0000
C
$
4
R
F
I
%
5
V
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
T
Observations
G
ANOVA
A
6
P-value
Lower 95%
2,520.8096 5.6656 0.000000916 9207.6625
337.0748 6.9792 0.00000001
1674.0025
391.3561 2.1184 0.039573837 41.2861
B
MacBook Pro
0.7352
0.5405
0.5205
2130.9497
49
Y
The
H
&
7
N
U
8
J
Hi
1
Significance F
1.7E-08
M
9
K
<
O
<
H
Upper 95 %
19,355.9156
3030.9953
1616.8041
0
L
command
Tables
P
>
Keypad
Submit Answer
:
1
{
option
[
?
1
"
@
}
1
dele
Transcribed Image Text:ck ^ ol Consider the following computer output of a multiple regression analysis relating annual salary to years of education and years of work experience. esc 1 1 A 1 option wer Ⓒ2022 Hawkes Learning Z ☺ @ 2 W S Coefficients Standard Error t Stat 14281.78907 2352.4989 829.0451 How much would you expect your salary to increase if you had one more year of education? X H command Intercept Education (Years) Experience (Years) # 3 E D df SS MS F Regression 2 245,665,739.0934 122,832,869.5467 27.0501 Residual 46 208,883,538.9066 Total 4,540,946.4980 48 454,549,278.0000 C $ 4 R F I % 5 V Regression Statistics Multiple R R Square Adjusted R Square Standard Error T Observations G ANOVA A 6 P-value Lower 95% 2,520.8096 5.6656 0.000000916 9207.6625 337.0748 6.9792 0.00000001 1674.0025 391.3561 2.1184 0.039573837 41.2861 B MacBook Pro 0.7352 0.5405 0.5205 2130.9497 49 Y The H & 7 N U 8 J Hi 1 Significance F 1.7E-08 M 9 K < O < H Upper 95 % 19,355.9156 3030.9953 1616.8041 0 L command Tables P > Keypad Submit Answer : 1 { option [ ? 1 " @ } 1 dele
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