Y is regressed against X1, X2, X3, X4, X5, and X6. Consider the following test: Ho: B1 = B2 = B3 = 0 Hj: one or more of the restrictions under Họ does not hold The sample size n = 8000. The computer computes the heteroskedasticity-robust F-statistic fo this test. The F-statistic is 2.90. What do you conclude? (R stands for reject and FTR stands for fail to reject.) R Ho at a = 0.20 R Ho at a = 0.15 R Ho at a = 0.10 R Ho at a = 0.05 R Ho at a = 0.0 R Ho at a = 0.20 R Ho at a = 0.15 R Ho at a = 0.10 R Ho at a = 0.05 FTR Ho at a -001
Y is regressed against X1, X2, X3, X4, X5, and X6. Consider the following test: Ho: B1 = B2 = B3 = 0 Hj: one or more of the restrictions under Họ does not hold The sample size n = 8000. The computer computes the heteroskedasticity-robust F-statistic fo this test. The F-statistic is 2.90. What do you conclude? (R stands for reject and FTR stands for fail to reject.) R Ho at a = 0.20 R Ho at a = 0.15 R Ho at a = 0.10 R Ho at a = 0.05 R Ho at a = 0.0 R Ho at a = 0.20 R Ho at a = 0.15 R Ho at a = 0.10 R Ho at a = 0.05 FTR Ho at a -001
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
![1.
Y is regressed against X1, X2, X3, X4, Xs, and X6. Consider the following test:
Ho: B1 = B2 = B3 = 0
Hj: one or more of the restrictions under H, does not hold
The sample sizen= 8000. The computer computes the heteroskedasticity-robust F-statistic for
this test. The F-statistic is 2.90. What do you conclude? (R stands for reject and FTR stands
for fail to reject.)
A)
R Ho at a =
0.20
R Ho at a =
= 0.15
R Ho at a = 0.10
R Ho at a =
R Ho at a = 0.01
R Ho at a =
0.20
R Ho at a =
0.15
R Ho at a = 0.10 | R Ho at a =
0.05
FTR Ho at
a = 0.01
FTR Ho at
C)
R Ho at a =
0.20
R Ho at a = 0.15
R Ho at a = 0.10
FTR Ho at
%3D
a = 0.05
= 0.01
D)
R Ho at a
= 0.20
R Ho at a = 0.15
FTR Ho at
FTR Ho at
FTR Ho at
0.10
0.05
= 0.01
a =
a =
a =
E)
R Ho at a =
0.20
FTR Ho at
FTR Ho at
FTR Ho at
FTR Ho at
= 0.01
a = 0.15
FTR Ho at
a =
= 0.10
= 0.05
a =
a
F)
FTR Họ at
FTR Ho at
FTR Ho at
FTR Ho at
a = 0.20
a = 0.15
a = 0.10
a = 0.05
a = 0.01
B)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F6871a655-6df9-491d-9e6a-d916a0d3d66e%2F4368f407-a039-4997-9370-1096969a8bbd%2Fpaifwos_processed.png&w=3840&q=75)
Transcribed Image Text:1.
Y is regressed against X1, X2, X3, X4, Xs, and X6. Consider the following test:
Ho: B1 = B2 = B3 = 0
Hj: one or more of the restrictions under H, does not hold
The sample sizen= 8000. The computer computes the heteroskedasticity-robust F-statistic for
this test. The F-statistic is 2.90. What do you conclude? (R stands for reject and FTR stands
for fail to reject.)
A)
R Ho at a =
0.20
R Ho at a =
= 0.15
R Ho at a = 0.10
R Ho at a =
R Ho at a = 0.01
R Ho at a =
0.20
R Ho at a =
0.15
R Ho at a = 0.10 | R Ho at a =
0.05
FTR Ho at
a = 0.01
FTR Ho at
C)
R Ho at a =
0.20
R Ho at a = 0.15
R Ho at a = 0.10
FTR Ho at
%3D
a = 0.05
= 0.01
D)
R Ho at a
= 0.20
R Ho at a = 0.15
FTR Ho at
FTR Ho at
FTR Ho at
0.10
0.05
= 0.01
a =
a =
a =
E)
R Ho at a =
0.20
FTR Ho at
FTR Ho at
FTR Ho at
FTR Ho at
= 0.01
a = 0.15
FTR Ho at
a =
= 0.10
= 0.05
a =
a
F)
FTR Họ at
FTR Ho at
FTR Ho at
FTR Ho at
a = 0.20
a = 0.15
a = 0.10
a = 0.05
a = 0.01
B)
Expert Solution
![](/static/compass_v2/shared-icons/check-mark.png)
Step 1
From the given information,
There are 3 variables restricted under null hypothesis.
That is, p=3
Numerator df=p=3
n=8000
Denominator df=n-(p+1)=8000-(3+1)=7996
P value:
F statistic=2.90
P=0.0336, obtained from the Excel function, =F.DIST.RT(2.9,3,7996).
Decision Rule:
If p-value ≤ α, then reject the null hypothesis.
If p-value > α, then do not reject the null hypothesis.
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