Use a 1% level of significance to test the claim that ρ < 0 (i) What are the null and alternative hypotheses? a.) H0: ρ = 0 and H1: ρ < 0 b.) H0: ρ = 0 and H1: ρ > 0 c.) H0: ρ < 0 and H1: ρ > 0 d.) H0: ρ > 0 and H1: ρ < 0 Part 2 (ii) Use a 1% level of significance to test the claim that ρ < 0 and what is the t-statistic?  a.) -7.03 (d.f.=5) b.) -10.07 (d.f.=6) c.) -10.07 (d.f.=5) d.) -7.03 (d.f.=6)

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Question 1-Part 1

Use a 1% level of significance to test the claim that ρ < 0

(i) What are the null and alternative hypotheses?

a.) H0: ρ = 0 and H1: ρ < 0

b.) H0: ρ = 0 and H1: ρ > 0

c.) H0: ρ < 0 and H1: ρ > 0

d.) H0: ρ > 0 and H1: ρ < 0

Part 2

(ii) Use a 1% level of significance to test the claim that ρ < 0 and what is the t-statistic? 

a.) -7.03 (d.f.=5)

b.) -10.07 (d.f.=6)

c.) -10.07 (d.f.=5)

d.) -7.03 (d.f.=6)

Part 3

(iii) Use a 1% level of significance to test the claim that ρ < 0 and what is the p-value? 

a.) .0005 < p-value < .005

b.) p-value < .0005

c.) .010 < p-value < .025

d.) .005 < p-value < .010

Part 4

(iv) Use a 1% level of significance to test the claim that ρ < 0 and what is your conclusion based on the p-value?

a.) At the 1% level of significance, we reject the null hypothesis. We have enough evidence to conclude that the population correlation coefficient between the depth of dive and the optimal time is negative.

b.) At the 1% level of significance, we fail to reject the null hypothesis. We do not have enough evidence to conclude that the population correlation coefficient between the depth of dive and the optimal time is negative.

c.) At the 1% level of significance, we reject the null hypothesis. We do not have enough evidence to conclude that the population correlation coefficient between the depth of dive and the optimal time is negative.

d.) At the 1% level of significance, we fail to reject the null hypothesis. We have enough evidence to conclude that the population correlation coefficient between the depth of dive and the optimal time is negative.

Part 5

Find a 90% confidence interval for β. Round to 3 decimal places.

a.) -0.388 < β < 0.280

b.) -.163 < β < 0.054

c.) -0.393 < β < 0.285

d.) -0.065 < β < -0.043

 

 
Scuba diving example (cont.)
What is the optimal amount of time for a scuba diver to be on the bottom of the
ocean? That depends on the depth of the dive. The U.S. Navy has done a lot of
research on this topic. The Navy defines the "optimal time" to be the time at each
depth for the best balance between length of work period and decompression time
after surfacing.
Let x = depth of dive in meters, and let y = optimal time in hours. A random sample of
7 divers show that there is a negative correlation between x and y. Below are the
regression results.
> summary(1mCy~x, scuba))
Call:
Im(formula - y ~ x, data - scuba)
Residuals:
1
2
3
5
7
-0.01880 0.03655 -0.14222 -0.25121 0.17659 0.12965 0.06943
Coefficients:
(Intercept) 3.366491
-0.054446
Estimate Std. Error t value Pr(>Itl)
20.05 5.7e-06 ***
-10.06 0.000166 ***
0.167904
Signif. codes: 0 ***** 0.001 **' 0.01 *' 0.05 '.' 0.1 ' '1
Residual standard error: 0.166 on 5 degrees of freedom
Multiple R-squared: 0.9529,
F-statistic: 101.2 on 1 and 5 DF, p-value: 0.0001662
Adjusted R-squared: 0.9435
Transcribed Image Text:Scuba diving example (cont.) What is the optimal amount of time for a scuba diver to be on the bottom of the ocean? That depends on the depth of the dive. The U.S. Navy has done a lot of research on this topic. The Navy defines the "optimal time" to be the time at each depth for the best balance between length of work period and decompression time after surfacing. Let x = depth of dive in meters, and let y = optimal time in hours. A random sample of 7 divers show that there is a negative correlation between x and y. Below are the regression results. > summary(1mCy~x, scuba)) Call: Im(formula - y ~ x, data - scuba) Residuals: 1 2 3 5 7 -0.01880 0.03655 -0.14222 -0.25121 0.17659 0.12965 0.06943 Coefficients: (Intercept) 3.366491 -0.054446 Estimate Std. Error t value Pr(>Itl) 20.05 5.7e-06 *** -10.06 0.000166 *** 0.167904 Signif. codes: 0 ***** 0.001 **' 0.01 *' 0.05 '.' 0.1 ' '1 Residual standard error: 0.166 on 5 degrees of freedom Multiple R-squared: 0.9529, F-statistic: 101.2 on 1 and 5 DF, p-value: 0.0001662 Adjusted R-squared: 0.9435
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