**Title: Analyzing Lemon Imports and Crash Fatality Rates****Introduction:**This exercise involves finding the regression equation by considering lemon imports as the predictor variable (x variable) and crash fatality rates as the response variable (y variable). The lemon imports are given in metric tons, and the crash fatality rates are per 100,000 people.**Data:**- **Lemon Imports (metric tons):** 231, 268, 354, 499, 546- **Crash Fatality Rate (per 100,000 people):** 16, 15.7, 15.4, 15.4, 15**Objective:**The goal is to calculate the best predicted crash fatality rate for a year with 400 metric tons of lemon imports using the regression equation. Additionally, the viability of the prediction is evaluated.**Required Steps:**1. **Find the equation of the regression line:** \[\hat{y} = a + b \cdot x\] Round the constant `a` to three decimal places and the coefficient `b` to six decimal places as needed.2. **Graph/Diagram Explanation:** While the image does not contain a graph, typically you would plot lemon imports on the x-axis and crash fatality rates on the y-axis to visualize the relationship. The regression line would represent the best fit line through these data points, illustrating the trend.**Conclusion:**After finding the regression equation, predict the crash fatality rate for 400 metric tons of lemon imports and assess the prediction's worthiness based on your analysis and potential real-world applications or limitations.

Given the data; Lemon Imports(X) Crash fatality rate(Y) (X¯-X) (Y¯-Y) (X¯-X)2 (X¯-X)(Y¯-Y) 231 16 148.6 -0.5 22081.96 -74.3 268 15.7 111.6 -0.2 12454.56 -22.32 354 15.4 25.6 0.1 655.36 2.56 499 15.4 -119.4 0.1 14256.36 -11.94 546 15 -166.4 0.5 27688.96 -83.2 1898 77.5 0 0 77137.2 -189.2 Mean of Crash Fatality Rate(Y) and Lemon Imports(X) is 15.5 and 379.6 respectively. For the given data, regression can be given as; Crash Fatality Rate=Constant + Slope*Lemon ImportsThe sum of fields are SSxx and SSXY. Now to calculate the regression coefficient, we divide the covariance of X and Y (SSXY) by the variance of X(SSxx). Slope=SSXYSSXX=-189.277137.2=-0.002452 Intercept= Mean(Y)-Slope*Mean(X) Intercept=15.5+0.0024*379.6=16.411 Hence the regression equation is- Crash Fatality Rate=16.411-0.002452*Lemon Imports For predicting crash fatality rate for a year in which there are 400 metric tons of lemon imports is; Crash Fatality Rate=16.411-0.002452*400=15.4302

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Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a year in which there are 400 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports 231 268 Crash Fatality Rate 16 15.7 354 546 D 15 499 15.4 15.4 Find the equation of the regression line. Round the constant three decimal places as needed. Round the coefficient to six decimal places as needed.)

Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a year in which there are 400 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports 231 268 Crash Fatality Rate 16 15.7 354 546 D 15 499 15.4 15.4 Find the equation of the regression line. Round the constant three decimal places as needed. Round the coefficient to six decimal places as needed.)

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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