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Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? 228 266 359 483 532 Lemon Imports Crash Fatality Rate 15.9 15.6 15.5 15.2 14.8 What are the null and alternative hypotheses? OA. Ho: p=0 OB. Ho: p=0 H₁: p=0 H₁: p<0 OC. Ho: p *0 OD. Ho: p=0 H₁: p=0 H₁: p>0 Construct a scatterplot. Choose the correct graph below. OA. O C. O D. Q 171 17- AY 17 Q 17- 16- Q 16- Q 15- 15- G 14 14- AY OB. AY 17- 16 15- 14 14+ H Q Q C tot o AY • a 1x 6 200 400 600 0 The linear correlation coefficient is r=. (Round to three decimal places as needed.) The test statistic is t= - (Round to three decimal places as needed.) The P-value is. (Round to three decimal places as needed.) Because the P-value is than the significance level 0.05, there Do the results suggest that imported lemons cause car fatalities? OA. The results suggest that an increase in imported lemons causes car fatality rates to remain the same. OB. The results suggest that imported lemons cause car fatalities. OC. The results do not suggest any cause-effect relationship between the two variables. O D. The results suggest that an increase in imported lemons causes in an increase in car fatality rates. H+ 16- too 15- 19 0 x X 14- 0 200 400 600 0 200 400 600 200 400 600 sufficient evidence to support the claim that there is a linear correlation between lemon imports and crash fatality rates for a significance level of a = 0.05. o 0 ++ G H 392 ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ ·* 0

Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? 228 266 359 483 532 Lemon Imports Crash Fatality Rate 15.9 15.6 15.5 15.2 14.8 What are the null and alternative hypotheses? OA. Ho: p=0 OB. Ho: p=0 H₁: p=0 H₁: p<0 OC. Ho: p *0 OD. Ho: p=0 H₁: p=0 H₁: p>0 Construct a scatterplot. Choose the correct graph below. OA. O C. O D. Q 171 17- AY 17 Q 17- 16- Q 16- Q 15- 15- G 14 14- AY OB. AY 17- 16 15- 14 14+ H Q Q C tot o AY • a 1x 6 200 400 600 0 The linear correlation coefficient is r=. (Round to three decimal places as needed.) The test statistic is t= - (Round to three decimal places as needed.) The P-value is. (Round to three decimal places as needed.) Because the P-value is than the significance level 0.05, there Do the results suggest that imported lemons cause car fatalities? OA. The results suggest that an increase in imported lemons causes car fatality rates to remain the same. OB. The results suggest that imported lemons cause car fatalities. OC. The results do not suggest any cause-effect relationship between the two variables. O D. The results suggest that an increase in imported lemons causes in an increase in car fatality rates. H+ 16- too 15- 19 0 x X 14- 0 200 400 600 0 200 400 600 200 400 600 sufficient evidence to support the claim that there is a linear correlation between lemon imports and crash fatality rates for a significance level of a = 0.05. o 0 ++ G H 392 ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ ·* 0

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. Construct a scatterplot, find the value of the linear correlation coefficient \( r \), and find the P-value using \( \alpha = 0.05 \). Is there sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? | Lemon Imports (metric tons) | Car Crash Fatality Rate (per 100,000 population) | |-----------------------------|-----------------------------------------------| | 228 | 15.9 | | 266 | 15.6 | | 359 | 15.5 | | 483 | 15.2 | | 532 | 14.8 | ### Hypothesis Testing **What are the null and alternate hypotheses?** - A. \( H_0: \rho = 0 \) \( H_1: \rho < 0 \) - B. \( H_0: \rho = 0 \) \( H_1: \rho \ne 0 \) - **C. \( H_0: \rho \ne 0 \) \( H_1: \rho = 0 \)** - D. \( H_0: \rho = 0 \) \( H_1: \rho > 0 \) ### Scatterplot Construction **Construct a scatterplot. Choose the correct graph below.** - **A.** ![Graph A](scatterplot_A.png) - B. ![Graph B](scatterplot_B.png) - C. ![Graph C](scatterplot_C.png) - D. ![Graph D](scatterplot_D.png) ### Calculation Details 1. **The linear correlation coefficient \( r \) is:** 2. **The test statistic \( t \) is:** 3. **The P-value is:** ### Conclusion Because the P-value is \( < / \ge / > \) than the significance level 0.05, there \( is / is not \) sufficient evidence to support the claim that there is a linear correlation between lemon imports and crash fatality rates for a significance level of \( \alpha = 0.05 \). ### Interpretation Do the results suggest that imported lemons cause car fatalities?
Transcribed Image Text:Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. Construct a scatterplot, find the value of the linear correlation coefficient \( r \), and find the P-value using \( \alpha = 0.05 \). Is there sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? | Lemon Imports (metric tons) | Car Crash Fatality Rate (per 100,000 population) | |-----------------------------|-----------------------------------------------| | 228 | 15.9 | | 266 | 15.6 | | 359 | 15.5 | | 483 | 15.2 | | 532 | 14.8 | ### Hypothesis Testing **What are the null and alternate hypotheses?** - A. \( H_0: \rho = 0 \) \( H_1: \rho < 0 \) - B. \( H_0: \rho = 0 \) \( H_1: \rho \ne 0 \) - **C. \( H_0: \rho \ne 0 \) \( H_1: \rho = 0 \)** - D. \( H_0: \rho = 0 \) \( H_1: \rho > 0 \) ### Scatterplot Construction **Construct a scatterplot. Choose the correct graph below.** - **A.** ![Graph A](scatterplot_A.png) - B. ![Graph B](scatterplot_B.png) - C. ![Graph C](scatterplot_C.png) - D. ![Graph D](scatterplot_D.png) ### Calculation Details 1. **The linear correlation coefficient \( r \) is:** 2. **The test statistic \( t \) is:** 3. **The P-value is:** ### Conclusion Because the P-value is \( < / \ge / > \) than the significance level 0.05, there \( is / is not \) sufficient evidence to support the claim that there is a linear correlation between lemon imports and crash fatality rates for a significance level of \( \alpha = 0.05 \). ### Interpretation Do the results suggest that imported lemons cause car fatalities?
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