Pls help I need in one hour thankyou **Predicting Crash Fatality Rates Using Lemon Imports**In this exercise, we are tasked with finding the regression equation, where the first variable (lemon imports in metric tons) acts as the predictor (x variable). The goal is to determine the best-predicted crash fatality rate per 100,000 people for a year in which there are 425 metric tons of lemon imports.### Data Provided:- **Lemon Imports (metric tons):** 232, 265, 351, 462, 538- **Crash Fatality Rate (per 100,000 people):** 16, 15.7, 15.4, 15.4, 14.9### Steps:1. **Find the Equation of the Regression Line:** - Format: \( \hat{y} = a + bx \) - Round the y-intercept (\(a\)) to three decimal places. - Round the slope (\(b\)) to four decimal places.2. **Calculate the Predicted Crash Fatality Rate:** - Input 425 metric tons of lemon imports into the regression equation. - Round to one decimal place.3. **Evaluate the Worthiness of the Prediction:** #### Options: - **A:** The sample size is small, making the prediction inappropriate. - **B:** All requirements for forming the regression line are met, making the prediction worthwhile. - **C:** The presence of an outlier makes the prediction inappropriate. - **D:** The relationship between the two variables is questionable, making the prediction illogical.This analysis helps in understanding the relationship between lemon imports and crash fatality rates, though common sense and statistical checks should guide the interpretation and trust in the prediction.

Solution To find regression equation use the following steps in excel.

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 yoar in which there are 425 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports 232 265 Crash Fatality Rate 16 15.7 15.4 351 462 15,4 14.9 538 D Find the equation of the regression line. (Round the y-intercept three decimal places as needed. Round the slope to four decimal places as needed.) The best predicted crash fatality rate for a year in which there are 425 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 the sample size is small, the prediction is not appropriate. O B. Since all of the requirements for finding the equation of the regression line are met, the prediction is worthwhile. OC. Since there appears to be an outlier, 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 yoar in which there are 425 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports 232 265 Crash Fatality Rate 16 15.7 15.4 351 462 15,4 14.9 538 D Find the equation of the regression line. (Round the y-intercept three decimal places as needed. Round the slope to four decimal places as needed.) The best predicted crash fatality rate for a year in which there are 425 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 the sample size is small, the prediction is not appropriate. O B. Since all of the requirements for finding the equation of the regression line are met, the prediction is worthwhile. OC. Since there appears to be an outlier, 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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Question

Pls help I need in one hour thankyou

**Predicting Crash Fatality Rates Using Lemon Imports**

In this exercise, we are tasked with finding the regression equation, where the first variable (lemon imports in metric tons) acts as the predictor (x variable). The goal is to determine the best-predicted crash fatality rate per 100,000 people for a year in which there are 425 metric tons of lemon imports.

### Data Provided:

- **Lemon Imports (metric tons):** 232, 265, 351, 462, 538
- **Crash Fatality Rate (per 100,000 people):** 16, 15.7, 15.4, 15.4, 14.9

### Steps:

1. **Find the Equation of the Regression Line:**
- Format: \( \hat{y} = a + bx \)
- Round the y-intercept (\(a\)) to three decimal places.
- Round the slope (\(b\)) to four decimal places.

2. **Calculate the Predicted Crash Fatality Rate:**
- Input 425 metric tons of lemon imports into the regression equation.
- Round to one decimal place.

3. **Evaluate the Worthiness of the Prediction:**

#### Options:
- **A:** The sample size is small, making the prediction inappropriate.
- **B:** All requirements for forming the regression line are met, making the prediction worthwhile.
- **C:** The presence of an outlier makes the prediction inappropriate.
- **D:** The relationship between the two variables is questionable, making the prediction illogical.

This analysis helps in understanding the relationship between lemon imports and crash fatality rates, though common sense and statistical checks should guide the interpretation and trust in the prediction.

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