A researcher attempts to study the effect of aviation connectivity on innovation using regression analysis. They gathered the following data in 2015, including inventors, the total number of inventors located in city i for patents registered in 2015, connectivity, a measure of global connectivity through aviation networks of city i's airports, Personal Income, the total personal income recorded for 2015 in City i, and Population, the level of population in 2015 in city i.
A researcher attempts to study the effect of aviation connectivity on innovation using regression analysis. They gathered the following data in 2015, including inventors, the total number of inventors located in city i for patents registered in 2015, connectivity, a measure of global connectivity through aviation networks of city i's airports, Personal Income, the total personal income recorded for 2015 in City i, and Population, the level of population in 2015 in city i.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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![Problem 1: Aviation and Innovation
A researcher attempts to study the effect of aviation connectivity on innovation using
regression analysis. They gathered the following data in 2015, including inventors, the total
number of inventors located in city i for patents registered in 2015, connectivity, a measure of
global connectivity through aviation networks of city i's airports, Personal Income, the total
personal income recorded for 2015 in City i, and Population, the level of population in 2015 in
city i.
. reg inventors connectivity Personal Income Population
Source
df
MS
Number of obs
526
F(3, 522)
236.47
Model
1.6167e+09
3
538888533
Prob > F
0.0000
Residual
1.1896e+09
522 2278847.84
R-squared
0.5761
Adj R-squared
adj_R2
%3D
Total
2.8062e+09
525
5345188.9
Root MSE
1509.6
%3D
inventors Coefficient Std. err.
t
P>|t|
[95% conf. interval]
t
CI-LB
CI-UB
connectivity
0356768
.0093273
le.e00
Personal_Income
0000563
6.92e-06
8.14
0.000
.0000427
.0000699
beta_3
70.32327
Population
.0003614
-5.08
0.000
-.0025461
-.0011261
_cons
74.57838
0.94
0.346
-76.18737
216.8339
a) Is this dataset cross-sectional, panel, or a time series? Why
b) Compute the 5 missing values in the regression table. Show your work.
c) Carefully interpret the regression coefficients and their statistical significance. Is this in line
with your expectations?
Page 3 of 14](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F36d93af9-1c60-4c54-a265-7600bbfc6b68%2F68a67b84-24c4-4071-bd27-b892146173fc%2Fhh7dgm_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Problem 1: Aviation and Innovation
A researcher attempts to study the effect of aviation connectivity on innovation using
regression analysis. They gathered the following data in 2015, including inventors, the total
number of inventors located in city i for patents registered in 2015, connectivity, a measure of
global connectivity through aviation networks of city i's airports, Personal Income, the total
personal income recorded for 2015 in City i, and Population, the level of population in 2015 in
city i.
. reg inventors connectivity Personal Income Population
Source
df
MS
Number of obs
526
F(3, 522)
236.47
Model
1.6167e+09
3
538888533
Prob > F
0.0000
Residual
1.1896e+09
522 2278847.84
R-squared
0.5761
Adj R-squared
adj_R2
%3D
Total
2.8062e+09
525
5345188.9
Root MSE
1509.6
%3D
inventors Coefficient Std. err.
t
P>|t|
[95% conf. interval]
t
CI-LB
CI-UB
connectivity
0356768
.0093273
le.e00
Personal_Income
0000563
6.92e-06
8.14
0.000
.0000427
.0000699
beta_3
70.32327
Population
.0003614
-5.08
0.000
-.0025461
-.0011261
_cons
74.57838
0.94
0.346
-76.18737
216.8339
a) Is this dataset cross-sectional, panel, or a time series? Why
b) Compute the 5 missing values in the regression table. Show your work.
c) Carefully interpret the regression coefficients and their statistical significance. Is this in line
with your expectations?
Page 3 of 14
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