**Correlation Analysis: Lemon Imports vs. 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.| Lemon Imports (metric tons) | Crash Fatality Rate (per 100,000 population) ||-----------------------------|---------------------------------------------|| 230 | 15.8 || 266 | 15.6 || 359 | 15.5 || 481 | 15.3 || 530 | 14.9 |Tasks:1. Construct a scatterplot using the given data.2. Calculate the linear correlation coefficient (\( r \)).3. Determine the p-value using \( \alpha = 0.05 \).Objectives:- Identify whether there is sufficient evidence to conclude a linear correlation between lemon imports and crash fatality rates.- Analyze the results to infer if imported lemons may have any causal effect on car crash fatalities.**Explanation:**To evaluate the relationship between these two variables, follow these steps:1. **Constructing the Scatterplot:** - Plot the lemon imports on the x-axis. - Plot the crash fatality rates on the y-axis. - Each pair of data points forms a coordinate (for example, (230, 15.8)).2. **Calculating the Correlation Coefficient (\( r \)):** - Use the formula for Pearson's correlation coefficient to find the strength and direction of the linear relationship.3. **Determining the P-Value:** - Use the calculated \( r \) to find the p-value. - Compare the p-value to the significance level \( \alpha = 0.05 \).**Analysis:**- Interpreting the correlation coefficient will inform you of the direction (positive or negative) and strength of the relationship.- A p-value less than 0.05 would indicate statistically significant evidence of a correlation.- However, correlation does not imply causation. Additional context and analysis are required to infer any causal relationships.Does the analysis suggest that imported lemons cause car fatalities? This investigation will require critical thinking and understanding of correlation vs. causation concepts.

The scatter plot is used to observe the relation in between variables. It consists of data points.…

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 359 15.5 530 14.9 230 266 481 15.8 15.6 15.3

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 359 15.5 530 14.9 230 266 481 15.8 15.6 15.3

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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