**Correlation Analysis between Lemon Imports and Car Crash Fatality Rates**Listed below are annual data for various years. The data represent the weights (in metric tons) of imported lemons and car crash fatality rates per 100,000 population. The aim is to construct a scatterplot to analyze the correlation and determine if there is a linear relationship between lemon imports and crash fatality rates. **Tasks:**1. Construct a scatterplot using the given data.2. Find the value of the linear correlation coefficient (r).3. Calculate the P-value with α = 0.05.4. Evaluate if the correlation suggests causation between lemon imports and car crash fatalities.**Data Table:**| Yearly Lemon Imports (Metric Tons) | Yearly Crash Fatality Rate (per 100,000) ||-------------------------------------|-------------------------------------------|| 232 | 15.9 || 264 | 15.7 || 357 | 15.4 || 484 | 15.3 || 530 | 14.8 |**Instructions:**1. **Scatterplot Construction:** - Plot the data points on a graph where the x-axis represents the annual lemon imports and the y-axis represents the car crash fatality rates per 100,000 population.2. **Linear Correlation Coefficient (r):** - Use the formula for the Pearson correlation coefficient to determine the strength and direction of the linear relationship between the two variables: \[ r = \frac{n(\sum xy) - (\sum x)(\sum y)}{\sqrt{[n\sum x^2 - (\sum x)^2][n\sum y^2 - (\sum y)^2]}} \]3. **P-Value Calculation:** - Determine the statistical significance of the linear correlation by finding the P-value. Using α = 0.05, evaluate if the correlation is statistically significant.4. **Analysis and Conclusion:** - Interpret the calculated r and P-value to analyze if there is a significant linear correlation between the weight of lemon imports and car crash fatality rates. - Discuss if the results suggest that imported lemons cause car crash fatalities or if an alternative explanation might be more plausible.**Note:**Correlation does not imply causation. Even if a significant linear relationship is found, it does not necessarily mean that

Let x be lemon Imports and y be Crash Fatality rate. x y 232 15.9 264 15.7 357 15.4 484…

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? Lemon Imports Crash Fatality Rate 357 15.4 484 15.3 530 14.8 232 264 15.9 15.7

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? Lemon Imports Crash Fatality Rate 357 15.4 484 15.3 530 14.8 232 264 15.9 15.7

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

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 α=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: 228 265 359 480 532 Crash Fatality Rates: 15.9 15.6 15.4 15.3 14.9 The linear correlation coefficient r is? The test statistic t is? The P-value is?
Listed below are the overhead widths (in cm) of seals measured from photographs and the weights (in kg) of the seals. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the critical values of r using a = 0.05, Is there sufficient evidence to conclude that there is a linear correlation between overhead widths of seals from photographs and the weights of the seals? Overhead Width 7.1 7.5 178 Click here to view a table of critical values for the correlation coefficient. 9.6 9.4 8.8 8.2 Weight 112 205 238 204 188 OA. YB. OC. KD D. Aweight (kg) 300- A weight (kg) Aweight (kg) 300- Aweight (kg) 300- 300- .. 100 100+ 100 7. rect: 0 10 10 10 10 width (om) width (cm) width (on) widn (om) The linear correlation coefficient is r= (Round to three decimal places as needed.) Enter your answer in the answer box and then click Check Answer. O parts remaining Check Answer वी
Listed below are amounts of court income and salaries paid to the town justices. All amounts are in thousands of dollars. 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 court incomes and justice salaries? Based on the results, does it appear that justices might profit by levying larger fines? Court Income 66.0 402.0 1568.01131.0 270.0 250.0 1 12.0 150.0 32.0 D Justice Salary 29 46 90 58 45 61 24 25 18 What are the null and alternative hypotheses? O A. Ho: p=0 О В. Но: р30 Hiip0 O D. Ho: p+0 H1: p = 0
Listed below are amounts of court income and salaries paid to the town justices. All amounts are in thousands of dollars. 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 court incomes and justice salaries? Based on the results, does it appear that justices might profit by levying larger fines? Court Income Justice Salary 65.0 403.0 1568.01132.0 271.0 252.0 112.0 150.0 34.0 e 60 31 42 91 57 46 24 25 17 Ο Α. Η : ρ=0, B. Ho: p=0 H:p#0 H,:p>0 O C. Ho: p=0 O D. Ho: pz0 H1:p=0 H,:p<0 Construct a scatterplot. Choose the correct graph below. O A. OB. Oc. C. D. AJustice Salary 100- Q AJustice Salary 100- AJustice Salary 100- AJustice Salary 100- Q .. 50- 50- 50- . 50- 50- . 0- 0- 0- 800 1600 800 1600 800 1600 800 1600 Court Income Court Income Court Income Court Income The linear correlation coefficient is r= 0.869 (Round to three decimal…
Listed below are the overhead widths (in cm) of seals measured from photographs and the weights (in kg) of the seals. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the critical values of r using a = 0.01. Is there sufficient evidence to conclude that there is a linear correlation between overhead widths of seals from photographs and the weights of the seals? Overhead Width 7.2 7.5 9.8 9.3 8.9 8.1 Weight 119 172 248 201 205 181 Click here to view a table of critical values for the correlation coefficient. Construct a scatterplot. Choose the correct graph below. A. В. OC. D. Aweight (kg) 300- Aweight (kg) 300- Aweight (kg) 300- Aweight (kg) 300- 100+ 1004 100- 100+ 10 7 10 7 10 7 10 width (cm) width (cm) width (cm) width (cm) The linear correlation coefficient is r= (Round to three decimal places as needed.) The critical values are r= (Round to three decimal places as needed. Use a comma to separate answers as needed.) Because the absolute…
Police sometimes measure shoe prints at crime scenes so that they can learn something about criminals. Listed below are shoe print lengths, foot lengths, and heights of males. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Based on these results, does it appear that police can use a shoe print length to estimate the height of a male? Use a significance level of a= 0.01. Shoe Print (cm) | 28.8 Foot Length (cm) 24.8 Height (cm) 30.8 30.4 31.1 28.6 24.6 27.8 26.1 25.3 177.6 179.2 179.2 169.4 169.5
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 corelation 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? non imports Crash Fatality Rate What are the null and alternative hypotheses? OA. Họ: p=0 H: p>0 OB. He: p=0 H:p<0 OC. He: p=0 H;: p#0 OD. H: pr0 H: p=0 Construct a scatterplot. Choose the correct graph below. OA OB. Oc. OD. 17 17 16 16 15 Click to select your answer(s).
Listed below are amounts of court income and salaries paid to the town justices. All amounts are in thousands of dollars. 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 court incomes and justice salaries? Based on the results, does it appear that justices might profit by levying larger fines? Court Income Justice Salary 65.0 406.0 1566.0 1131.0 274.0 253.0 110.0 152.0 31.0 e 29 45 94 58 46 61 25 26 19 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.) V than the significance level 0.05, there court incomes and justice salaries for a significance level of a = 0.05. Because the P-value is V sufficient evidence to support the claim that there is a linear correlation between Based…
Listed below are annual data for various years. The data are the numbers of cars sold (thousands) and the numbers of points scored in the Super Bowl. 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 those two variables? Would it be reasonable to expect a correlation? Car Sales 8170 8220 8510 9000 8640 8526 8273 8144 Super Bowl Points 61 70 42 76 45 55 55 53 What are the null and alternative hypotheses? OA. Ho p=0 H₁: p>0 OC. Ho p=0 H₁: p<0 Construct a scatterplot. Choose the correct graph below. OA. 100- 8000 Car Sales 9000 The linear correlation coefficient is r= 0.193 (Round to three decimal places as needed.) The test statistic is t=0.48. (Round to two decimal places as needed.) The P-value is (Round to three decimal places as needed.) OB. Ho: p#0 H₁: p=0 D. Ho: p=0 H₁: p 0 O B. ○ D. 100- Q 100- Q 100+ Q 50- 0+ 8000 9000 Car Sales…
After gathering data about the number of starfish and measuring the pollution in areas of the ocean you find a negative linear correlation between pollution levels and number of starfish. What can you conclude based on this information? a. There is a confounding variable that is affecting both pollution and starfish. b. As pollution rises the number of starfish falls c. That pollution is causing starfish to die, leading to the negative correlation d. That pollution is supporting starfish, leading to the negative correlation
Listed below are amounts of court income and salaries paid to the town justices. All amounts are in thousands of dollars. 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 court incomes and justice salaries? Based on the results, does it appear that justices might profit by levying larger fines? Court Income 65.0 406.0 1567.0 1131.0 271.0 254.0 111.0 152.0 30.0 Justice Salary 29 45 91 58 45 60 24 25 19 What are the null and alternative hypotheses? O A. Ho: p#0 O B. Ho: p=0 H₁: p=0 H₁: p0 H₁: p=0 Construct a scatterplot. Choose the correct graph below. A. B. C. ★Justice Salary AJustice Salary 100- Justice Salary D. 100- ★Justice Salary 100+ ▬▬▬▬▬▬ · ■● 50- 50- 50+ 0- 0- 800 1600 800 1600 Court Income Court Income Court Income Court Income The linear correlation coefficient is r = (Round to three decimal places as needed.) The test…
The blood pressure measurements of a single patient were taken by twelve different medical students and the results are listed below. 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 systolic measurements and diastolic measurements? systolic (x) diastolic (y) 137 133 139 119 122 121 127 132 130 143 141 137 95 93 100 80 88 80 82 84 81 98 103 94 С. Но: р#0 D. Ho: p=0 H1:p=0 H1:p#0 Construct a scatterplot. Choose the correct graph below. O A. ОВ. C. D. Ay 160- Ay 160- 160- 160- 120- 120- 120- 120- 80- 80- 80- 80- O. 40- 40- 40- 40- X X 0- 0- O 40 80 120 160 0- 0- 40 80 120 160 40 80 120 160 40 80 120 160 The linear correlation coefficient r is (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 sufficient evidence to support the…