## Regression Analysis of Lemon Imports and Crash Fatality Rates### Problem StatementThe task is to find the regression equation, letting the first variable be the predictor (x) variable. Given the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, we need to determine the best-predicted crash fatality rate for a year in which there are 500 metric tons of lemon imports. Finally, we need to evaluate if the prediction is worthwhile.### Data| Lemon Imports (Metric Tons) | Crash Fatality Rate (per 100,000 people) ||-----------------------------|------------------------------------------|| 226 | 16.1 || 265 | 16.0 || 365 | 15.7 || 476 | 15.5 || 539 | 15.1 |### ExplanationThe table presents two sets of data:1. **Lemon Imports**: This variable shows the amount of lemon imports in metric tons.2. **Crash Fatality Rate**: This variable represents the number of crash fatalities per 100,000 people.The objective is to use this data to develop a regression equation that can predict the crash fatality rate based on lemon imports. In this context, lemon imports will serve as the independent variable (x), and the crash fatality rate will be the dependent variable (y). ### Steps to Follow1. **Determine the Regression Equation**: - Calculate the means of both variables. - Compute the slope (b) and the y-intercept (a) of the regression line using the least squares method. - Formulate the regression equation of the form \( y = a + bx \).2. **Prediction for 500 Metric Tons**: - Use the regression equation to predict the crash fatality rate when lemon imports are 500 metric tons.3. **Evaluation of the Prediction**: - Assess the correlation and causation between lemon imports and crash fatality rates. - Consider residuals and potential errors.Developing a clear understanding of these steps will enable us to make informed predictions and recognize the potential limitations of such correlations.

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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 500 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports Crash Fatality Rate 16.1 226 265 539 O 365 15.7 476 15.5 16 15,1

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 500 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports Crash Fatality Rate 16.1 226 265 539 O 365 15.7 476 15.5 16 15,1

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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