How would you interpret this data
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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Question
How would you interpret this data?
![Standard coefficients from multiple regression analyses for incarceration rate predicting child
health outcomes in the U.S. (Omitted poverty rate)
Infant Mortality
Child Mortality
Incarceration rate
Unemployment
rates
.0530446*
-.0023066
Household income
Education level -
Some
Education level -
None
Total population
N
R2
ljusted R2
F
*Significant at 95% confidence level
-.061347*
-.4781141*
.0486091
.2378367*
176
0.9880
0.9873
1356.41
.4512338*
-.1217312
-.3782457*
-.7162724
1.013728
-.9331809
176
0.4593
0.4265
14.01
Teen Mortality
.3817716*
-.1382288
-.2170069*
-.6915968
.1901228
-.5092064
176
0.5503
0.5230
20.19
Pre-term Birth
-.0337045*
.0051691
.0465859*
.4593045*
-.2245987*
.1389805*
176
0.9938
0.9934
2636.36
Low Birth Weight
-.1653476*
-.0920173
.4909464*
-.8866794
1.036614*
-1.866877*
176
0.5776
0.5520
22.57](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F8dd902f8-6431-45e1-964f-aabc90f93bf5%2Fb93b588f-ed42-4f06-ae98-89cacdb401fa%2Ftc5ii1q_processed.png&w=3840&q=75)
Transcribed Image Text:Standard coefficients from multiple regression analyses for incarceration rate predicting child
health outcomes in the U.S. (Omitted poverty rate)
Infant Mortality
Child Mortality
Incarceration rate
Unemployment
rates
.0530446*
-.0023066
Household income
Education level -
Some
Education level -
None
Total population
N
R2
ljusted R2
F
*Significant at 95% confidence level
-.061347*
-.4781141*
.0486091
.2378367*
176
0.9880
0.9873
1356.41
.4512338*
-.1217312
-.3782457*
-.7162724
1.013728
-.9331809
176
0.4593
0.4265
14.01
Teen Mortality
.3817716*
-.1382288
-.2170069*
-.6915968
.1901228
-.5092064
176
0.5503
0.5230
20.19
Pre-term Birth
-.0337045*
.0051691
.0465859*
.4593045*
-.2245987*
.1389805*
176
0.9938
0.9934
2636.36
Low Birth Weight
-.1653476*
-.0920173
.4909464*
-.8866794
1.036614*
-1.866877*
176
0.5776
0.5520
22.57
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