> cegre=lnCHeight wat) > summary (regres) call: Jn(formula Height - wat) Residuals: Min -20. 229-2.624 10Median 1.456 3Q мах 4.561 10. 364 coolm Coefficients: (Intercept) 93.21610511.625314 Wat Estimate std. Error t value Pr (>|t|) 8.018 5.97e-09 *** 6.455 3.94e-07 ** * 0. 024691 0.003825 signif. codes: 0 ***** 0.001 ***' 0.01 **' 0.05 '.' 0.1 1 www Residual standard error: 7.393 on 30 degrees of freedom Multiple R-squared: 0.5814, F-statistic: 41. 67 on 1 and 30 DER-value: 3.938e-07 Adjusted R-squared: 0. 5674 > confint (reares) 2.5 % (Intercept) 69.47404650 116. 95816271 0. 01687938 97.5 % wat 0.03250356
> cegre=lnCHeight wat) > summary (regres) call: Jn(formula Height - wat) Residuals: Min -20. 229-2.624 10Median 1.456 3Q мах 4.561 10. 364 coolm Coefficients: (Intercept) 93.21610511.625314 Wat Estimate std. Error t value Pr (>|t|) 8.018 5.97e-09 *** 6.455 3.94e-07 ** * 0. 024691 0.003825 signif. codes: 0 ***** 0.001 ***' 0.01 **' 0.05 '.' 0.1 1 www Residual standard error: 7.393 on 30 degrees of freedom Multiple R-squared: 0.5814, F-statistic: 41. 67 on 1 and 30 DER-value: 3.938e-07 Adjusted R-squared: 0. 5674 > confint (reares) 2.5 % (Intercept) 69.47404650 116. 95816271 0. 01687938 97.5 % wat 0.03250356
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
Based on this confidence interval, is there a significant linear relation between Height and Weight?
![> cegre=lnCHeight wat)
> summary (regres)
call:
Jn(formula
Height - wat)
Residuals:
Min
-20. 229-2.624
10Median
1.456
3Q
мах
4.561
10. 364
coolm
Coefficients:
(Intercept) 93.21610511.625314
Wat
Estimate std. Error t value Pr (>|t|)
8.018 5.97e-09 ***
6.455 3.94e-07 ** *
0. 024691
0.003825
signif. codes: 0 ***** 0.001 ***' 0.01 **' 0.05 '.' 0.1 1
Residual standard error: 7.393 on 30 degrees of freedom
Multiple R-squared: 0.5814,
F-statistic: 41. 67 on 1 and 30 DER-value: 3.938e-07
Adjusted R-squared: 0. 5674
> confint (regres)
2.5 %
97.5 %
(Intercept) 69.47404650 116.95816271
wat
0. 01687938
0.03250356](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fd62ed927-e496-498b-a40a-a0df908413d5%2Fb449ea96-c34f-49cf-b73f-7d16b570cf77%2F4umaszi_processed.png&w=3840&q=75)
Transcribed Image Text:> cegre=lnCHeight wat)
> summary (regres)
call:
Jn(formula
Height - wat)
Residuals:
Min
-20. 229-2.624
10Median
1.456
3Q
мах
4.561
10. 364
coolm
Coefficients:
(Intercept) 93.21610511.625314
Wat
Estimate std. Error t value Pr (>|t|)
8.018 5.97e-09 ***
6.455 3.94e-07 ** *
0. 024691
0.003825
signif. codes: 0 ***** 0.001 ***' 0.01 **' 0.05 '.' 0.1 1
Residual standard error: 7.393 on 30 degrees of freedom
Multiple R-squared: 0.5814,
F-statistic: 41. 67 on 1 and 30 DER-value: 3.938e-07
Adjusted R-squared: 0. 5674
> confint (regres)
2.5 %
97.5 %
(Intercept) 69.47404650 116.95816271
wat
0. 01687938
0.03250356
Expert Solution
![](/static/compass_v2/shared-icons/check-mark.png)
Introduction
We have to decide that if linear relationship is significant or not based on confidence interval .
Step by step
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