o perform a test to determine whether we have a significant linear relationship using an F test, your friend tells you to compute a two-sided p-value. Is this correct and why?

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To perform a test to determine whether we have a significant linear relationship using an F test, your friend tells you to compute a two-sided p-value. Is this correct and why?

 

A study on the relationship between Infant mortality rate and the overall Child death rate in the 50 states in the U.S
was conducted. In the data, the sample variance of Child death rate is 225.538, while the average Infant mortality
rate is 7.126. The model output for this relationship fit in R is presented below.
Call:
1m(formula = Infant. mort
~ CDR, data =
data)
Residuals:
Min
10 Median
30
Маx
-1.6281 -0.7550 -0.1228
0.7810
2.0451
Coefficients:
Estimate Std. Error t value Pr(>[t])
(Intercept) 5.729936
0.274961
20.84
< 2e-16 ***
CDR
0.057736
0.009687
(C)
(D) ***
Signif. codes:
O *** 0.001 ** 0.01 * 0.05 . 0.1 1
Residual standard error: (B) on 48 degrees of freedom
Multiple R-squared: (A),Adjusted R-squared:
F-statistic: 35.52 on 1 and 48 DF,
0.4133
p-value: 2.883e-07
Transcribed Image Text:A study on the relationship between Infant mortality rate and the overall Child death rate in the 50 states in the U.S was conducted. In the data, the sample variance of Child death rate is 225.538, while the average Infant mortality rate is 7.126. The model output for this relationship fit in R is presented below. Call: 1m(formula = Infant. mort ~ CDR, data = data) Residuals: Min 10 Median 30 Маx -1.6281 -0.7550 -0.1228 0.7810 2.0451 Coefficients: Estimate Std. Error t value Pr(>[t]) (Intercept) 5.729936 0.274961 20.84 < 2e-16 *** CDR 0.057736 0.009687 (C) (D) *** Signif. codes: O *** 0.001 ** 0.01 * 0.05 . 0.1 1 Residual standard error: (B) on 48 degrees of freedom Multiple R-squared: (A),Adjusted R-squared: F-statistic: 35.52 on 1 and 48 DF, 0.4133 p-value: 2.883e-07
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