11 **Title: Regression Analysis of Lemon Imports and Crash Fatality Rates**---**Objective:**Find the regression equation with lemon imports (in metric tons) as the predictor (x) variable to estimate the crash fatality rate (per 100,000 people). Determine the predicted fatality rate for a year with 475 metric tons of lemon imports and assess the prediction's validity.**Data Provided:**| Lemon Imports (Metric Tons) | Crash Fatality Rate (per 100,000 People) ||-----------------------------|------------------------------------------|| 228 | 16 || 262 | 15.9 || 362 | 15.7 || 466 | 15.5 || 512 | 14.9 |**Task:**Determine the equation of the regression line:\[ \hat{y} = b_0 + b_1x \]- **Calculate coefficients:** - \( b_0 \): y-intercept (round to three decimal places) - \( b_1 \): slope (round to four decimal places)**Application:**- Use the regression equation to find the predicted crash fatality rate for 475 metric tons of lemon imports.- Evaluate whether this prediction is worthwhile based on the analysis.---By following these steps, you will understand how lemon imports potentially correlate with crash fatality rates and refine predictive models accordingly.

Given data, X Y X*Y X*X 228 16 3648 51984 262 15.9 4165.8 68644 362 15.7 5683.4 131044…

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 the best predicted crash fatality rate for a year in which there are 475 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports Crash Fatality Rate 16 15.9 228 262 362 466 512 0 15.7 15.5 14.9 ..... Find the equation of the regression line.