Correlations calculated in 9.2 INFMORT INCOME OLDMOM YOUNGMOM Pearson Correlation Sig. (2-tailed) N TOOSOON Pearson Correlation. Sig. (2-tailed) N CONTRACE Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N INFMORT 1 . 26 -.556** .003 26 .224 .271 26 -.049 .811 26 .123 .549 26 -.440* .025 26 Correlations INCOME **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). -.556** .003 26 1 26 .057 .782 26 .042 .840 26 -.140 .495 26 .329 .100 26 YOUNGMOM 9.5 What can we conclude from data on infant mortality? .224 .271 26 .057 .782 26 1 26 -.5781 .002 26 .008 .970 26 .302 .134 26 OLDMOM -.049 .811 26 .042 .840 26 -.578 .002 26 1 26 -.194 .342 26 -.142 .489 26 TOOSOON .123 .549 26 -.140 .495 26 .008 .970 26 -.194 .342 26 1 . 26 -.320 .111 26 CONTRACE -.440* .025 26 .329 .100 26 .302 .134 26 -.142 .489 26 -.320 .111 26 1 * 26 9.8 From the previous, do you think that we are able to conclude that low income causes infant mortality?
Correlations calculated in 9.2 INFMORT INCOME OLDMOM YOUNGMOM Pearson Correlation Sig. (2-tailed) N TOOSOON Pearson Correlation. Sig. (2-tailed) N CONTRACE Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N INFMORT 1 . 26 -.556** .003 26 .224 .271 26 -.049 .811 26 .123 .549 26 -.440* .025 26 Correlations INCOME **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). -.556** .003 26 1 26 .057 .782 26 .042 .840 26 -.140 .495 26 .329 .100 26 YOUNGMOM 9.5 What can we conclude from data on infant mortality? .224 .271 26 .057 .782 26 1 26 -.5781 .002 26 .008 .970 26 .302 .134 26 OLDMOM -.049 .811 26 .042 .840 26 -.578 .002 26 1 26 -.194 .342 26 -.142 .489 26 TOOSOON .123 .549 26 -.140 .495 26 .008 .970 26 -.194 .342 26 1 . 26 -.320 .111 26 CONTRACE -.440* .025 26 .329 .100 26 .302 .134 26 -.142 .489 26 -.320 .111 26 1 * 26 9.8 From the previous, do you think that we are able to conclude that low income causes infant mortality?
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
Pavannn
Transcribed Image Text:Correlations calculated in 9.2
INFMORT
INCOME
YOUNGMOM
OLDMOM
TOOSOON
CONTRACE
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
INFMORT
1
.
26
-.556**
.003
26
.224
.271
26
-.049
.811
26
.123
.549
26
-.440*
.025
26
Correlations
INCOME
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
-.556**
.003
26
1
26
.057
.782
26
.042
.840
26
-.140
.495
26
.329
.100
26
YOUNGMOM
9.5 What can we conclude from data on infant mortality?
.224
.271
26
.057
.782
26
1
26
-.578**
.002
26
.008
.970
26
.302
.134
26
OLDMOM
-.049
.811
26
.042
.840
26
-.578*1
.002
26
1
26
-.194
.342
26
-.142
.489
26
TOOSOON
.123
.549
26
-.140
.495
26
.008
.970
26
-.194
.342
26
1
26
-.320
.111
26
CONTRACE
-.440*
.025
26
.329
.100
26
.302
.134
26
-.142
.489
26
-.320
.111
26
1
.
26
9.8 From the previous, do you think that we are able to conclude that low income causes infant
mortality?
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