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 and find the value of the linear correlation coefficient r. 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? Construct a scatterplot. Choose the correct graph below. O A. Ay 17- 16- 15 14+ 0 。 。 C Lemon Imports Crash Fatality Rate O 0 0 200 400 600 Q Q G 232 15.9 OB. Aу 17 16- 15- 14+ Tel O + 264 15.6 0 200 400 600 Q G 357 15.5 481 15.3 O C. Ay 17- 16- 15- 14+ 534 14.9 19 T The linear correlation coefficient ris (Round to three decimal places as needed.) 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? OA. The results suggest that an increase in imported lemons causes car fatality rates to remain the same. OB. The results do not suggest any cause-effect relationship between the two variables. OC. The results suggest that imported lemons cause car fatalities. O D. The results suggest that an increase in imported lemons causes in an increase in car fatality rates. o 200 400 600 B O D. Ay 17- 16- 15- 14- 0 O 。 200 400 600 Q G

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
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Chapter4: Equations Of Linear Functions
Section4.5: Correlation And Causation
Problem 2AGP
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### Correlation Between Lemon Imports and Car Crash Fatality Rates

---

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 and find the value of the linear correlation coefficient \( r \). 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?

#### Data Table:

| Lemon Imports (Metric Tons) | Crash Fatality Rate (per 100,000 population) |
|-----------------------------|----------------------------------------------|
| 232                         | 15.9                                         |
| 264                         | 15.6                                         |
| 357                         | 15.5                                         |
| 481                         | 15.3                                         |
| 534                         | 14.9                                         |

#### Scatterplot Selection:

Construct a scatterplot. Choose the correct graph below.

- **Option A:**

  ![Scatterplot A](link/to/scatterplotA)

- **Option B:**

  ![Scatterplot B](link/to/scatterplotB)

- **Option C:**

  ![Scatterplot C](link/to/scatterplotC)

- **Option D:**

  ![Scatterplot D](link/to/scatterplotD)

#### Determining the Linear Correlation Coefficient:

Calculate the linear correlation coefficient \( r \). (Round to three decimal places as needed.)

\[ r = \_\_\_\_\_\_ \]

#### Conclusion:

There \(\_\_\_\_\_\_\_\) sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates.

#### Analyzing the Results:

Do the results suggest that imported lemons cause car fatalities?

- **A.** The results suggest that an increase in imported lemons causes car fatality rates to remain the same.
- **B.** The results do not suggest any cause-effect relationship between the two variables.
- **C.** The results suggest that imported lemons cause car fatalities.
- **D.** The results suggest that an increase in imported lemons causes an increase in car fatality rates.

#### Explanation of Graphs:

- **Option A:** Displays no clear linear trend; dots are scattered without any specific direction.
- **Option B:** Displays a downward trend indicating a potential negative
Transcribed Image Text:### Correlation Between Lemon Imports and Car Crash Fatality Rates --- 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 and find the value of the linear correlation coefficient \( r \). 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? #### Data Table: | Lemon Imports (Metric Tons) | Crash Fatality Rate (per 100,000 population) | |-----------------------------|----------------------------------------------| | 232 | 15.9 | | 264 | 15.6 | | 357 | 15.5 | | 481 | 15.3 | | 534 | 14.9 | #### Scatterplot Selection: Construct a scatterplot. Choose the correct graph below. - **Option A:** ![Scatterplot A](link/to/scatterplotA) - **Option B:** ![Scatterplot B](link/to/scatterplotB) - **Option C:** ![Scatterplot C](link/to/scatterplotC) - **Option D:** ![Scatterplot D](link/to/scatterplotD) #### Determining the Linear Correlation Coefficient: Calculate the linear correlation coefficient \( r \). (Round to three decimal places as needed.) \[ r = \_\_\_\_\_\_ \] #### Conclusion: There \(\_\_\_\_\_\_\_\) sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates. #### Analyzing the Results: Do the results suggest that imported lemons cause car fatalities? - **A.** The results suggest that an increase in imported lemons causes car fatality rates to remain the same. - **B.** The results do not suggest any cause-effect relationship between the two variables. - **C.** The results suggest that imported lemons cause car fatalities. - **D.** The results suggest that an increase in imported lemons causes an increase in car fatality rates. #### Explanation of Graphs: - **Option A:** Displays no clear linear trend; dots are scattered without any specific direction. - **Option B:** Displays a downward trend indicating a potential negative
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