QUESTION 33 Under assumptions MLR1-6, all our included variables are (approximately) normally distributed. a. True b. False QUESTION 34 Omitting a variable from our model that has a causal effect on our dependent variable always leads to omitted variable bias. a. False O b. True QUESTION 35 In a panel dataset we observe the same individual multiple times. O True O False
QUESTION 33 Under assumptions MLR1-6, all our included variables are (approximately) normally distributed. a. True b. False QUESTION 34 Omitting a variable from our model that has a causal effect on our dependent variable always leads to omitted variable bias. a. False O b. True QUESTION 35 In a panel dataset we observe the same individual multiple times. O True O False
Chapter1: Making Economics Decisions
Section: Chapter Questions
Problem 1QTC
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Question
Please all solve the question
Transcribed Image Text:QUESTION 33
Under assumptions MLR1-6, all our included variables are (approximately) normally distributed.
a. True
O b. False
QUESTION 34
Omitting a variable from our model that has a causal effect on our dependent variable always leads to omitted
variable bias.
a. False
O b. True
QUESTION 35
In a panel dataset we observe the same individual multiple times.
True
O False
![QUESTION 44
Consider the following regression estimates (FN7)
Source
SS
df
MS
Number of obs
526
%3D
F(3, 522)
74.67
%3D
Model
44.5393713
14.8464571
Prob > F
0.0000
%3D
R-squared
Adj R-squared
Residual
103.79038
522
.198832146
0.3003
%3D
0.2963
Total
148.329751
525
.28253286
Root MSE
.44591
%3D
lwage
Coef.
Std. Err.
t
P>|t|
[95% Conf. Interval]
educ
.0903658
.007468
12.10
0.000
.0756948
.1050368
exper
.0410089
.0051965
7.89
0.000
0308002
.0512175
exper2
-.0007136
.0001158
-6.16
0.000
-.000941
-.0004861
_cons
.1279975
.1059323
1.21
0.227
-.0801085
.3361035
where Iwage is the natural logarithm of hourly wage in US$, educ is years of education, exper is years of work
experience and exper2 is experience squared (exper * exper).
What is the exact effect in percent of a 15 years increase in education on predicted wage?
State your answer in percentages. For example, if you think the answer is 10% write 10 instead of 0.1. Do not use the %
symbol.
QUESTION 45
Consider the following scenario:
• The significance level is 5%
• Of all tested hypotheses, 10% are true
• The statistical power is 60%
What is the probability of the finding being true, given that the estimate is statistically significant?
(State your answer as percentage without the percent symbol. For example, if you think the correct answer is 10%, just
state 10)
QUESTION 32
Consider the following dataset:
y.
х1
x2
34
1
55
2
33
3
72
4
5
It is possible to regress x1 on y.
a. True
O b. False](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F6ec0f649-f7a6-461c-a960-8b6b7f0dfe51%2F02645800-8bd7-4f7a-a3a9-c4d5d3a9a9fe%2Fvxrjlgt_processed.jpeg&w=3840&q=75)
Transcribed Image Text:QUESTION 44
Consider the following regression estimates (FN7)
Source
SS
df
MS
Number of obs
526
%3D
F(3, 522)
74.67
%3D
Model
44.5393713
14.8464571
Prob > F
0.0000
%3D
R-squared
Adj R-squared
Residual
103.79038
522
.198832146
0.3003
%3D
0.2963
Total
148.329751
525
.28253286
Root MSE
.44591
%3D
lwage
Coef.
Std. Err.
t
P>|t|
[95% Conf. Interval]
educ
.0903658
.007468
12.10
0.000
.0756948
.1050368
exper
.0410089
.0051965
7.89
0.000
0308002
.0512175
exper2
-.0007136
.0001158
-6.16
0.000
-.000941
-.0004861
_cons
.1279975
.1059323
1.21
0.227
-.0801085
.3361035
where Iwage is the natural logarithm of hourly wage in US$, educ is years of education, exper is years of work
experience and exper2 is experience squared (exper * exper).
What is the exact effect in percent of a 15 years increase in education on predicted wage?
State your answer in percentages. For example, if you think the answer is 10% write 10 instead of 0.1. Do not use the %
symbol.
QUESTION 45
Consider the following scenario:
• The significance level is 5%
• Of all tested hypotheses, 10% are true
• The statistical power is 60%
What is the probability of the finding being true, given that the estimate is statistically significant?
(State your answer as percentage without the percent symbol. For example, if you think the correct answer is 10%, just
state 10)
QUESTION 32
Consider the following dataset:
y.
х1
x2
34
1
55
2
33
3
72
4
5
It is possible to regress x1 on y.
a. True
O b. False
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