Question
In: Statistics and Probability
5. Please find below regression output for regression of Height on Shoesize and a New variable....
5. Please find below regression output for regression of Height on Shoesize and a New variable. interpret the following regression output, i.e. comment on
RSquare, Significance F, p-values of the two independent variables. (20)
|
SUMMARY OUTPUT |
|||||||
|
Regression Statistics |
|||||||
|
Multiple R |
0.962912 |
||||||
|
R Square |
0.9272 |
||||||
|
Adjusted RSquare |
0.913963 |
||||||
|
Standard Error |
1.723551 |
||||||
|
Observations |
14 |
||||||
|
ANOVA |
|||||||
|
df |
SS |
MS |
F |
Significance F |
|||
|
Regression |
2 |
416.1802 |
208.0901 |
70.04916 |
5.52E-07 |
||
|
Residual |
11 |
32.67693 |
2.97063 |
||||
|
Total |
13 |
448.8571 |
|||||
|
Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
||
|
Intercept |
21.84225 |
6.996671 |
3.121807 |
0.009719 |
6.442685 |
37.24182 |
|
|
Shoesize |
1.276756 |
0.367657 |
3.472686 |
0.005215 |
0.467549 |
2.085963 |
|
|
New_Var |
0.450635 |
0.133383 |
3.378511 |
0.006159 |
0.157062 |
0.744209 |
|
Solutions
orchestra answered 2 years agoRelated Solutions
Shown below is a portion of an Excel output for regression analysis relating Y (dependent variable)...
Shown below is a portion of an Excel output for regression
analysis relating Y (dependent variable) and X (independent
variable).
ANOVA
df
SS
Regression
1
39947.80
Residual (Error)
10
8280.81
Total
11
48228.61
Coefficients
Standard Error
t Stat
P-value
Intercept
69.190
26.934
2.569
0.02795
X
2.441
0.351
6.946
0.00004
1. What is the estimated regression equation
that relates Y to X? (2 Points)
2. Is the regression relationship significant?
Use the p-value approach and alpha = 0.05 to answer this question.
(2...
Find the regression equation, letting the first variable be the predictor (x) variable. Find the best...
Find the regression equation, letting the first variable be the
predictor (x) variable. Find the best predicted Nobel Laureate
rate for a country that has 78.1.
Internet users per 100 people. How does it compare to the
country's actual Nobel Laureate rate of 1.6 per 10 million
people?
Find the equation of the regression line.
Y^= _____ + ______x.
(Round the constant to one decimal place as needed. Round the
coefficient to three decimal places as needed.)
The best predicted...
Find the regression equation, letting the first variable be the predictor (x) variable. Find the best...
Find the regression equation, letting the first variable be the
predictor (x) variable. Find the best predicted Nobel Laureate
rate for a country that has 78.2 Internet users per 100 people. How
does it compare to the country's actual Nobel Laureate rate of 1
per 10 million people?
Internet Users Per 100 Nobel Laureates
79.5 5.5
80.6 24.2
77.8 8.7
45 0.1
82.7 6.1
37.9 0.1
89.2 25.3
88.9 7.6
79.8 9
83.6 12.8
52.8 1.9
77.3 12.7
56.5 3.3...
3.Below is the regression input and output (from Excel) for the regression in which the percentage...
3.Below is the regression input and output (from Excel) for the
regression in which the percentage change in the exchange rate is
the dependent variable (Y) and the inflation differential
(inflation rate home – inflation rate foreign) is the independent
variable (X). According to the Purchasing Power Parity theory, the
hypothesized coefficients (null hypothesis) in the regression are 0
(intercept coefficient) and 1 (inflation differential
coefficient). The directions for Problem Set 1 instruct
you to first read sections of the...
The following output was obtained from a regression analysis of the dependent variable Rating and an...
The following output was obtained from a regression analysis of
the dependent variable Rating and an independent variable Price.
(10 points)
ANOVA
df
SS
MS
F
Regression
1
372.707
372.707
42.927
Residual
15
130.234
8.682
Total
16
502.941
Coefficients
Standard Error
t Stat
P-value
Intercept
45.623
3.630
12.569
0.000
Price
0.107
0.016
6.552
0.000
Use the critical value approach to perform an F test for the
significance of the linear relationship between Rating and Price at
the 0.05 level of...
A.) Find the regression equation, letting the first variable be the predictor (x) variable. Using the...
A.) Find the regression equation, letting the first variable be
the predictor (x) variable. Using the listed actress/actor ages
in variousyears, find the best predicted age of the Best Actor
winner given that the age of the Best Actress winner that year is
34 years. Is the result within 5 years of the actual Best Actor
winner, whose age was 52 years?
Best Actress
29
29
29
58
34
33
46
28
64
23
45
54
Best Actor
44
37...
The following regression output was obtained from a study of architectural firms. The dependent variable is...
The following regression output was obtained from a study of
architectural firms. The dependent variable is the total amount of
fees in millions of dollars.
Predictor
Coefficient
SE Coefficient
t
p-value
Constant
7.617
2.998
2.541
0.010
x1
0.224
0.069
3.246
0.000
x2
?
1.144
0.559
?
2.047
0.028
x3
?
0.071
0.120
?
0.592
0.114
x4
0.675
0.354
1.907
0.001
x5
?
0.057
0.025
?
2.280
0.112
Analysis of
Variance
Source
DF
SS
MS
F
p-value
Regression
5
2,113.40
422.7...
The following regression output was obtained from a study of architectural firms. The dependent variable is...
The following regression output was obtained from a study of
architectural firms. The dependent variable is the total amount of
fees in millions of dollars.
Predictor
Coefficient
SE Coefficient
t
p-value
Constant
7.617
2.998
2.541
0.010
x1
0.224
0.069
3.246
0.000
x2
?
1.144
0.559
?
2.047
0.028
x3
?
0.071
0.120
?
0.592
0.114
x4
0.675
0.354
1.907
0.001
x5
?
0.057
0.025
?
2.280
0.112
Analysis of
Variance
Source
DF
SS
MS
F
p-value
Regression
5
2,113.40
422.7...
The following regression output was obtained from a study of architectural firms. The dependent variable is...
The following regression output was obtained from a study of
architectural firms. The dependent variable is the total amount of
fees in millions of dollars.
Predictor
Coefficient
SE Coefficient
t
p-value
Constant
7.131
3.085
2.312
0.010
x1
0.203
0.170
1.194
0.000
x2
−
1.176
0.553
−
2.127
0.028
x3
−
0.089
0.311
−
0.286
0.114
x4
0.682
0.381
1.790
0.001
x5
−
0.030
0.025
−
1.200
0.112
Analysis of Variance
Source
DF
SS
MS
F
p-value
Regression
5
1,946.79
389.4...
The following regression output was obtained from a study of architectural firms. The dependent variable is...
The following regression output was obtained from a study of
architectural firms. The dependent variable is the total amount of
fees in millions of dollars.
Predictor
Coefficient
SE
T
P-vaule
Constant
7.096
3.245
2.187
0.010
x1
0.222
0.117
1.897
0.000
x2
-1.024
0.562
-1.822
0.028
x3
-0.337
0.192
-1.755
0.114
x4
0.623
0.263
2.369
0.001
x5
-0.056
0.029
-2.000
0.112
Analysis of Variance
Source
DF
SS
MS
F
P-Value
Regression
5
2009.28
401.9
7.33
0.000
Residual Error
50
2741.54
54.83...
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