**Understanding Regression Analysis with Lemon Imports and Crash Fatality Rates****Task Explanation:**The objective is to find the regression equation, using lemon imports as the predictor (x) variable. The data pairs lemon imports in metric tons and crash fatality rates per 100,000 people. The goal is to predict the crash fatality rate for a year with 475 metric tons of lemon imports, and assess if this prediction is worthwhile.**Data Presented:**- Lemon Imports (Metric Tons): 226, 260, 354, 488, 511- Crash Fatality Rate (Per 100,000 People): 16, 15.7, 15.4, 15.4, 15**Steps to Obtain the Regression Equation:**1. **Find the Equation of the Regression Line:** - Use the formula $\hat{y} = a + bx$. - $a$ represents the y-intercept (round to three decimal places). - $b$ is the slope coefficient (round to six decimal places).2. **Prediction for Given Data:** - Determine the best predicted crash fatality rate when lemon imports are 475 metric tons (round to one decimal place).3. **Evaluate Prediction Worth:** - Options to consider regarding the prediction's validity: - **A:** All regression line requirements met; prediction is worthwhile. - **B:** Lack of logical relationship suggests prediction is nonsensical. - **C:** Presence of an outlier makes prediction inappropriate. - **D:** Small sample size renders prediction inappropriate.**Conclusion:**After inserting the required calculations, select the most reasonable answer regarding the prediction's worthiness.

From given data, X Y X*Y X*X 226 16 3616 51076 260 15.7 4082 67600 354 15.4 5451.6 125316 488 15.4 7515.2 238144 511 15 7665 261121 Since all of the requirements for finding the equation of the regression line are met, the prediction is worthwhile

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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 475 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports Crash Fatality Rate 16 15.7 226 260 354 488 511 O 15.4 15.4 15 Find the equation of the regression line. (Round the constant three decimal places as needed. Round the coefficient to six decimal places as needed.) The best predicted crash fatality rate for a year in which there are 475 metric tons of lemon imports is fatalities per 100,000 population. (Round to one decimal place as needed.) Is the prediction worthwhile? O A. Since all of the requirements for finding the equation of the regression line are met, the prediction is worthwhile. OB. Since common sense suggests there should not be much of a relationship between the two variables, the prediction does not make much sense. O C. Since there appears to be an outlier, the prediction is not appropriate. O D. Since the sample size is small, the prediction is not appropriate.

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 475 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports Crash Fatality Rate 16 15.7 226 260 354 488 511 O 15.4 15.4 15 Find the equation of the regression line. (Round the constant three decimal places as needed. Round the coefficient to six decimal places as needed.) The best predicted crash fatality rate for a year in which there are 475 metric tons of lemon imports is fatalities per 100,000 population. (Round to one decimal place as needed.) Is the prediction worthwhile? O A. Since all of the requirements for finding the equation of the regression line are met, the prediction is worthwhile. OB. Since common sense suggests there should not be much of a relationship between the two variables, the prediction does not make much sense. O C. Since there appears to be an outlier, the prediction is not appropriate. O D. Since the sample size is small, the prediction is not appropriate.

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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