Bighom sheep are beautiful wild animals found throughout the western United States. Let x be the a9e of a bighom sheep (in years), and let y be the mortality rate (percent that die) for this age group. For example, x = 1, y = 14 means that 14% of the bighom sheep between 1 and 2 years old died. A random sample of Arizona bighom sheep gave the following information:

X 1 2 3 4 5

y 1 2.2 20.5 14.4 19.6 20.0

(b)Find the equation of the least-squares line. (Round your answers to two decimal places.

(c) Find r. Find the coefficient of determination. (Round your answers to three decimal places.)4/21/2020

Explain what these measures mean in the context of the problem.

Both the correlation coefficient r and coefficient of determinationmeasure the strength of the linear relationship between a bighom sheep's age and the mortality rate.

The correlation coefficient r measures the strength of the linear relationship between a bighom sheep's age and the

mortality rate. The coefficient of determinationmeasures the explained variation in mortality rate by the corresponding variation in age of a bighom sheep.

The coefficient of determination r measures the strength of the linear relationship beMeen a bighom sheep's age and the

mortality rate. The correlation coefficientmeasures the explained variation in mortality rate by the corresponding variation in age of a bighom sheep.

The correlation coefficientmeasures the strength of the linear relationship between a bighom sheep's age and the mortality rate. The coefficient of determination r measures the explained variation in mortality rate by the corresponding variation in age of a bighom sheep.

(d)Test the claim that the population correlation coefficient is positive at the 1/< level of significance. (Round your test statistic to three decimal places.)

Find or estimate the P-value of the test statistic.

P-value > 0.250

0.125 < P-value < 0.250 I

0.100 < P-value 0.125

0.075 < P-value < 0.100

C 0.050 < P-value < 0.075

0.025 < P-value < 0.050

0.010 < P-value < 0.025

0.005 < P-value < 0.010

0.0005 < P-value < 0.005

P-value < 0.0005

Conclusion

Rejet the null hypothesis, there is sufficient evidence that p > 0.

Reject the null hypothesis, there is insufficient evidence that p > 0.

Fail to reject the null hypothesis, there Is sufficient evidence that p > 0.

Fail to reject the null hypothesis, there Is insufficient evidence that p > 0.

(e)Given the result from part (c), is it practical to find estimates of y for a given x value based on the least-squares line model? Explain.

Given the lack of significance of r, prediction from the least-squares model might be misleading.

Given the lack of significance of r, prediction from the least-squares model is practical.

Given the significance of r, prediction from the least-squares model is practical.

Given the significance of r, prediction from the least-squares model might be misleading.