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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 15.7 15.5 512 O 14.9 Find the equation of the regression line. y= 16.790 +(-0.0033')x (Round the y-intercept to 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 475 metric tons of lemon imports is (Round to one decimal place as needed) fatalities per 100,000 population.

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 15.7 15.5 512 O 14.9 Find the equation of the regression line. y= 16.790 +(-0.0033')x (Round the y-intercept to 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 475 metric tons of lemon imports is (Round to one decimal place as needed) fatalities per 100,000 population.

MATLAB: An Introduction with Applications
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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**Regression Analysis on Lemon Imports and Crash Fatality Rates** The goal is to find the regression equation that best describes the relationship between lemon imports and crash fatality rates. The lemon imports are measured in metric tons, while the crash fatality rates are recorded per 100,000 people. ### Data - **Lemon Imports (Metric Tons):** 228, 262, 362, 466, 512 - **Crash Fatality Rate (Per 100,000 People):** 16, 15.9, 15.7, 15.5, 14.9 ### Regression Equation The regression equation is given by: \[ \hat{y} = 16.790 + (-0.0033)x \] - **Intercept (\(b_0\))** is rounded to three decimal places: 16.790 - **Slope (\(b_1\))** is rounded to four decimal places: -0.0033 ### Prediction Calculate the best predicted crash fatality rate for a year with 475 metric tons of lemon imports. ### Answer 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. **Graph Interpretation** While the image does not contain a graph, a scatter plot of lemon imports versus crash fatality rates, with the regression line, would typically show a downward slope, indicating that as lemon imports increase, the crash fatality rate slightly decreases.
Transcribed Image Text:**Regression Analysis on Lemon Imports and Crash Fatality Rates** The goal is to find the regression equation that best describes the relationship between lemon imports and crash fatality rates. The lemon imports are measured in metric tons, while the crash fatality rates are recorded per 100,000 people. ### Data - **Lemon Imports (Metric Tons):** 228, 262, 362, 466, 512 - **Crash Fatality Rate (Per 100,000 People):** 16, 15.9, 15.7, 15.5, 14.9 ### Regression Equation The regression equation is given by: \[ \hat{y} = 16.790 + (-0.0033)x \] - **Intercept (\(b_0\))** is rounded to three decimal places: 16.790 - **Slope (\(b_1\))** is rounded to four decimal places: -0.0033 ### Prediction Calculate the best predicted crash fatality rate for a year with 475 metric tons of lemon imports. ### Answer 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. **Graph Interpretation** While the image does not contain a graph, a scatter plot of lemon imports versus crash fatality rates, with the regression line, would typically show a downward slope, indicating that as lemon imports increase, the crash fatality rate slightly decreases.
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