Questions: Fifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying display. Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight? Use a significance level of α=0.05. Determine the null and alternative hypotheses. H0: p=□ H1: ρ> Identify the correlation coefficient, r. r= □ Identify the critical value(s). A. There are two critical values at r= ± □ B. There is one critical value at r= □ Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and their chest sizes? Choose the correct answer below and, if necessary, fill in the answer box within your choice. A. Yes, because the correlation coefficient □ falls outside the critical value(s). B. No, because the correlation coefficient □ falls outside the critical value(s). C. No, because the correlation coefficient □ falls between the critical values. D. Yes, because the correlation coefficient □ falls between the critical values. E. The answer cannot be determined from the given information. When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight? A. Yes, it is easier to measure a chest size than a weight because measuring weight would require lifting the bear onto the scale. The chest size could not be used to predict weight because there is not a linear correlation between the two. B. Yes, it is easier to measure a chest size than a weight because measuring weight would require lifting the bear onto the scale. The chest size could be used to predict weight because there is a linear correlation between the two. C. No, it is easier to measure weight than chest size because the chest is not a flat surface. D. Yes, it is easier to measure a chest size than a weight because measuring weight would require lifting the bear onto the scale. The chest size could not be used to predict weight because there is too much variance in the weight of the bears.

Fifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying display. Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight? Use a significance level of α=0.05.

Determine the null and alternative hypotheses.

H0: p=□
H1: ρ>

Identify the correlation coefficient, r.
r= □

Identify the critical value(s).

A. There are two critical values at r= ± □
B. There is one critical value at r= □
Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and their chest sizes? Choose the correct answer below and, if necessary, fill in the answer box within your choice.

A. Yes, because the correlation coefficient □ falls outside the critical value(s).
B. No, because the correlation coefficient □ falls outside the critical value(s).
C. No, because the correlation coefficient □ falls between the critical values.
D. Yes, because the correlation coefficient □ falls between the critical values.
E. The answer cannot be determined from the given information.

When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight?

A. Yes, it is easier to measure a chest size than a weight because measuring weight would require lifting the bear onto the scale. The chest size could not be used to predict weight because there is not a linear correlation between the two.
B. Yes, it is easier to measure a chest size than a weight because measuring weight would require lifting the bear onto the scale. The chest size could be used to predict weight because there is a linear correlation between the two.
C. No, it is easier to measure weight than chest size because the chest is not a flat surface.
D. Yes, it is easier to measure a chest size than a weight because measuring weight would require lifting the bear onto the scale. The chest size could not be used to predict weight because there is too much variance in the weight of the bears.
Transcript text: Fifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying display. Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight? Use a significance level of $\alpha=0.05$. Determine the null and alternative hypotheses. \[ \begin{array}{l} H_{0}: p=\square \\ H_{1}: \rho> \end{array} \] Identify the correlation coefficient, r. $r=$ $\square$ Identify the critical value(s). A. There are two critical values at $\mathrm{r}= \pm$ $\square$ B. There is one critical value at $\mathrm{r}=$ $\square$ Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and their chest sizes? Choose the correct answer below and, if necessary, fill in the answer box within your choice. A. Yes, because the correlation coefficient $\square$ falls outside the critical value(s). B. No, because the correlation coefficient $\square$ falls outside the critical value(s). C. No, because the correlation coefficient $\square$ falls between the critical values. D. Yes, because the correlation coefficient $\square$ falls between the critical values. E. The answer cannot be determined from the given information. When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight? A. Yes, it is easier to measure a chest size than a weight because measuring weight would require lifting the bear onto the scale. The chest size could not be used to predict weight because there is not a linear correlation between the two. B. Yes, it is easier to measure a chest size than a weight because measuring weight would require lifting the bear onto the scale. The chest size could be used to predict weight because there is a linear correlation between the two. C. No, it is easier to measure weight than chest size because the chest is not a flat surface. D. Yes, it is easier to measure a chest size than a weight because measuring weight would require lifting the bear onto the scale. The chest size could not be used to predict weight because there is too much variance in the weight of the bears.
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Solution

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Solution Steps

Step 1: Hypotheses

The null and alternative hypotheses for testing the correlation between the weights of bears and their chest sizes are defined as follows: \[ H_{0}: p = 0 \quad \text{(no correlation)} \] \[ H_{1}: p > 0 \quad \text{(positive correlation)} \]

Step 2: Correlation Coefficient

The calculated correlation coefficient \( r \) is: \[ r = 0.96 \]

Step 3: Critical Values

The critical values for the correlation coefficient at a significance level of \( \alpha = 0.05 \) are: \[ \text{Critical values} = \pm 0.268 \]

Step 4: Evidence of Correlation

To determine if there is sufficient evidence to support the claim of a linear correlation, we compare the absolute value of the correlation coefficient to the critical values: \[ |r| = 0.96 > 0.268 \] Since \( |r| \) falls outside the critical value(s), we conclude: \[ \text{Yes, because the correlation coefficient } 0.96 \text{ falls outside the critical value(s).} \]

Final Answer

The final conclusions are:

  • The correlation coefficient \( r \) is \( 0.96 \).
  • The critical values are \( \pm 0.268 \).
  • There is sufficient evidence to support the claim of a linear correlation.

Thus, the answer is boxed as follows: \[ \boxed{r = 0.96, \text{ critical values } = \pm 0.268, \text{ evidence supports correlation}} \]

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