Question
In: Statistics and Probability
Consider data regarding a response y and an explanatory variable x, both numeric x y 1...
Consider data regarding a response y and an explanatory variable x, both numeric
|
x |
y |
|
|
1 |
2.8 |
0.7 |
|
2 |
2.6 |
1.3 |
|
3 |
6.8 |
-1.1 |
|
4 |
3.0 |
0.2 |
|
5 |
4.7 |
1.1 |
|
6 |
5.0 |
-0.1 |
|
7 |
5.0 |
0.9 |
|
8 |
2.9 |
1.0 |
|
9 |
7.0 |
-0.2 |
|
10 |
3.7 |
0.8 |
The null hypothesis that the expected value of the response is constant for all values of the explanatory variable is:
Select one:
a. Not rejected with a significance level of 5%.
b. Rejected with a significance level of 5%, but not with a significance level of 1%.
c. Rejected with a significance level of 1%, but not with a significance level of 0.1%.
d. Rejected with a significance level of 0.1%
Solutions
orchestra answered 11 months agoRelated Solutions
Consider a binary response variable y and an explanatory variable x. The following table contains the...
Consider a binary response variable y and an
explanatory variable x. 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
−0.78
−5.90
(0.03
)
(0.03
)
x
0.04
0.28
(0.07
)
(0.02
)
a. Test for the significance of the intercept and
the slope coefficients at the 5% level in both models.
Coefficients
LPM
Logit
Intercept
Slope
b. What is the...
Consider a binary response variable y and an explanatory variable x. The following table contains the...
Consider a binary response variable y and an
explanatory variable x. 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
−0.70
−6.60
(0.03
)
(0.03
)
x
0.04
0.18
(0.04
)
(0.03
)
a. Test for the significance of the intercept and
the slope coefficients at the 5% level in both models.
coefficient
LPM
Logit
intercept
slope
b. What is the...
17.3 Consider a binary response variable y and an explanatory variable x. The following table contains...
17.3
Consider a binary response variable y and an
explanatory variable x. 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
−0.69
−6.30
(0.04)
(0.06)
x
0.05
0.15
(0.07)
(0.06)
a.
Test for the significance of the intercept and the slope
coefficients at a 5% level in both models.
Coefficients
LPM
Logit...
Collect data on one response (dependent or y) variable and two different explanatory (independent or x)...
Collect data on one response (dependent or y) variable and two
different explanatory (independent or x) variables. This will
require a survey with three questions. For example: To predict a
student’s GPA (y), you might collect data on two x variables: SAT
score and age. So we would be trying to determine if there was a
linear correlation between someone’s SAT score and their GPA, as
well as their age and their GPA. (Note: students may not choose GPA
as...
Collect data on one response (dependent or y) variable and two different explanatory (independent or x)...
Collect data on one response (dependent or y) variable and two
different explanatory (independent or x) variables. This will
require a survey with three questions. For example: To predict a
student’s GPA (y), you might collect data on two x variables: SAT
score and age. So we would be trying to determine if there was a
linear correlation between someone’s SAT score and their GPA, as
well as their age and their GPA. (Note: students may not choose GPA
as...
a)By hand, draw a scatter diagram treating x as the explanatory variable and y as the response variable
x
4
5
6
8
9
y
6
8
11
14
16
a)By hand, draw a scatter diagram treating x as the explanatory
variable and y as the response variable
b)Find the equation of the line containing the points (44,66)
and (9,16).
c)Graph the line found in part (b) on the scatter diagram.
d)By hand, determine the least-squares regression line.
e)Graph the least-squares regression line on the scatter
diagram.
f)Compute the sum of the squared residuals for the line found...
Suppose we have the following data on a dependent variable (Y) and an explanatory variable (X):...
Suppose we have the following data on a dependent variable (Y)
and an explanatory variable (X):
X Y
0 140
1 140
4 0
0 180
3 80
2 120
4 0
1 200
2 120
3 40
Calculate the simple linear regression equation by hand. Show
all your work. Using your result, predict the value of Y when X =
3.5. (15 points)
Calculate the R2and the adjusted
R2measures (by hand) and provide an interpretation of
what they tell us. (12 points)
Test (by hand) to see whether this is...
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...
1) In each scenario below, specify each variable as a response variable, an explanatory variable, or...
1) In each scenario below, specify each variable as a response
variable, an explanatory variable, or neither.
a. A researcher collects measurements of VO2 max and resting
heart rate on a group of
subjects to study the relationship between these two variables.
b. A real estate agent wants to be able to predict selling
prices of houses in Vancouver. He
collects data on 100 recently sold houses, recording their selling
prices, size, age, number
of bedrooms, and whether they had...
Here is data with y as the response variable. x y 71.4 25.1 82.8 34.4 81...
Here is data with y as the response variable.
x
y
71.4
25.1
82.8
34.4
81
75.3
77.1
72.8
84.6
63.4
64.8
75.8
85.4
117.6
-14.1
173.3
76.7
51.2
63.3
140.8
Make a scatter plot of this data. Which point is an outlier?
Enter as an ordered pair, e.g., (x,y).
(x,y)=
Find the regression equation for the data set
without the outlier. Enter
the equation of the form mx+b rounded to three decimal
places.
ˆywo=
Find the regression equation for...
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