Question
In: Statistics and Probability
Generate and provide the full regression output using x1, x2, their squared terms, and their interaction, as 'x' variables against the 'y' variable.
| X1 | X2 | Y |
| 10 | 3 | 2002 |
| 5 | 14 | 1747 |
| 8 | 4 | 1980 |
| 7 | 4 | 1902 |
| 6 | 7 | 1842 |
| 7 | 6 | 1883 |
| 4 | 21 | 1697 |
| 11 | 4 | 2021 |
| 5 | 12 | 1750 |
| 6 | 8 | 1832 |
| 5 | 18 | 1795 |
| 7 | 4 | 1917 |
| 8 | 5 | 1943 |
| 6 | 9 | 1830 |
| 5 | 12 | 1786 |
A.
| Generate and provide the full regression output using x1, x2, their squared terms, and their interaction, as 'x' variables against the 'y' variable. |
Solutions
orchestra answered 3 years agoRelated Solutions
Using Excel generate a simple regression model with Y as the dependent variable and X1 and...
Using Excel generate a simple regression model with Y
as the dependent variable and X1 and X2 as the independent
variables in the attached spreadsheet.
Write the following from the output:
Intercept:
Coefficients of Independent variable:
R-square:
Significance F:
Based on the model generated, forecast profits for a firm with
X1= Based on the model generated, forecast profits for a firm with
x1=250 and X2=100.
Evaluate the predictability of the model using explanatory
language that someone who does not have...
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...
Ten observations on the response variable y associated with two regressor variables x1 and x2 are...
Ten observations on the response variable y associated with two
regressor variables x1 and x2 are given in the following table. The
model fitted to these observations is yi = β 0 + β 1x1i + β 2x2i +
εi , i = 1, …, n , (3) where ε’s are identically and independently
distributed as a normal random variable with mean zero and a known
variance σ ^2 = 3. Observation # y x1 x2 1 7 9 1...
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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