Question
In: Statistics and Probability
For the table below, if Y is the dependent variable and X1 and X2 are the...
For the table below, if Y is the dependent variable and X1 and X2 are the independent variables. Using the linear regression equation Y=-0.45X1-1.34X2+15.67, which observation has the largest absolute residual?
|
Observation number |
Actual Y |
x1 |
X2 |
|
1 |
4.5 |
6.8 |
6.1 |
|
2 |
3.7 |
8.5 |
5.1 |
|
3 |
5 |
9 |
5 |
|
4 |
5.1 |
6.9 |
5.4 |
|
5 |
7 |
8 |
4 |
|
6 |
5.7 |
8.4 |
5.4 |
|
The first observation |
||
|
The third observation |
||
|
The fifth observation |
||
|
The second observation |
Solutions
Expert Solution
The answer is:
The residual output is:
The regression run in excel is:
Let me know in the comments if anything is not clear. I will reply ASAP! Please do upvote if satisfied!
orchestra answered 2 years agoRelated Solutions
For the table below, if Y is the dependent variable and X1 and X2 are the...
For the table below, if Y is the dependent variable and X1 and
X2 are the independent variables. Using the linear regression
equation Y=-0.45X1-1.34X2+15.67, find the Sum of
Squared Residuals? (choose the best answer)
Observation number
Actual Y
x1
X2
1
4.5
6.8
6.1
2
3.7
8.5
5.1
3
5
9
5
4
5.1
6.9
5.4
5
7
8
4
6
5.7
8.4
5.4
2.57
2.97
3.2
3.5
Using Y as the dependent variable and X1, X2, X3, X4 and X5 as the explanatory...
Using Y as the dependent variable and X1, X2, X3, X4 and X5 as
the explanatory variables, formulate an econometric model for data
that is (i) time series data (ii) cross-sectional data and (iii)
panel data – (Hint: please specify the specific model here not its
general form).
Consider the following data for a dependent variable y and two independent variables, x2 and x1....
Consider the following data for a dependent variable y and two
independent variables, x2 and x1.
x1 x2 y
30 12 94
46 10 109
24 17 113
50 17 179
41 5 94
51 19 175
75 8 171
36 12 118
59 13 143
77 17 212
Round your all answers to two decimal places. Enter negative
values as negative numbers, if necessary.
a. Develop an estimated regression equation relating y to x1 .
Predict y if x1=45....
Consider the following data for a dependent variable y and two independent variables, x1 and x2.
You may need to use the appropriate technology to answer this question.
Consider the following data for a dependent variable y and two independent variables,
x1 and x2.
x1
x2
y
30
12
93
47
10
108
25
17
112
51
16
178
40
5
94
51
19
175
74
7
170
36
12
117
59
13
142
76
16
211
The estimated regression equation for these data is
ŷ = −18.89 + 2.02x1 + 4.74x2.
Here, SST = 15,276.0,...
Use the dependent variable (labeled Y) and one of the independent variables (labeled X1, X2, and...
Use the dependent variable (labeled Y) and one of the
independent variables (labeled X1, X2, and X3) in the data file.
Select and use one independent variable throughout this analysis.
Use Excel to perform the regression and correlation analysis to
answer the following.
Generate a scatterplot for the specified dependent variable (Y)
and the selected independent variable (X), including the graph of
the "best fit" line. Interpret.
Determine the equation of the "best fit" line, which describes
the relationship between...
Use the dependent variable (labeled Y) and one of the independent variables (labeled X1, X2, and...
Use the dependent variable (labeled Y) and one of the
independent variables (labeled X1, X2, and X3) in the data file.
Select and use one independent variable throughout this analysis.
Use Excel to perform the regression and correlation analysis to
answer the following. The week 6 spreadsheet can be helpful in this
work.
1. Generate a scatterplot for the specified dependent variable
(Y) and the selected independent variable (X), including the graph
of the "best fit" line. Interpret.
2 Determine...
Consider the following data for a dependent variable y and two independent variables, x1 and x2....
Consider the following data for a dependent variable y
and two independent variables, x1 and
x2.
x1
x2
y
30
12
94
47
10
108
25
17
112
51
16
178
40
5
94
51
19
175
74
7
170
36
12
117
59
13
142
76
16
209
The estimated regression equation for these data is ŷ =
−17.02 + 1.99x1 +
4.70x2.
Here, SST = 14,902.9, SSR = 13,773.1,
sb1 =
0.2470, and
sb2 =
0.9480.
(1a) Test...
Consider the following data for a dependent variable y and two independent variables, x1 and x2....
Consider the following data for a dependent variable y
and two independent variables, x1 and
x2.
x1
x2
y
30
13
95
46
10
108
25
18
113
50
16
179
40
5
95
51
20
176
74
7
170
36
12
117
59
13
142
77
16
211
Round your all answers to two decimal places. Enter negative
values as negative numbers, if necessary.
a. Develop an estimated regression equation
relating y to x1.
ŷ =_________ +___________ x1
Predict...
Consider the following data for a dependent variable y and two independent variables, x1 and x2....
Consider the following data for a dependent variable y
and two independent variables, x1 and x2.
x1
x2
y
30
12
95
47
10
108
25
17
112
51
16
178
40
5
94
51
19
175
74
7
170
36
12
117
59
13
142
76
16
212
The estimated regression equation for these data is
ŷ = −18.52 + 2.01x1 +
4.75x2.
Here, SST = 15,234.1, SSR = 14,109.8,
sb1 =
0.2464, and
sb2 =
0.9457.
(a)Test for...
Consider a binary response variable y and two explanatory variables x1 and x2. The following table...
Consider a binary response variable y and two
explanatory variables x1 and
x2. The following table contains the parameter
estimates of the linear probability model (LPM) and the logit
model, with the associated p-values shown in
parentheses.
Variable
LPM
Logit
Constant
−0.40
−2.20
(0.03
)
(0.01
)
x1
0.32
0.98
(0.04
)
(0.06
)
x2
−0.04
−0.20
(0.01
)
(0.01
)
a. At the 5% significance level, comment on the
significance of the variables for both models.
Variable
LPM
Logit...
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