## 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.

Answered: Image /qna-images/answer/4e470b5e-31db-435d-bdeb-f1faf09fedab.jpg

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

See similar textbooks

Similar questions

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 425 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports Crash Fatality Rate 227 269 365 469 514 16 15.9 15.5 15.4 14.9 ..... Find the equation of the regression line. V = + (Round the y-intercept to three decimal places as needed. Round the slope to four decimal places as needed.)
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 231 262 354 500 536 Crash Fatality Rate 16 15.9 15.6 15.4 15
11
A simple regression model for 10 pair of data resulted in a standard error of 3.95 (i.e., Se = 3.95), and the. The sum of squares of error (SSE) is ______. a. 187.23 b. 171.63 c. 156.03 d. 140.42 e. 124.82
Use the pizza cost and the subway fare in the table below to find the regression equation, letting pizza cost be the predictor (x) variable. (Pizza cost is in dollars per slice, subway fare and CPI are in dollars.) What is the best predicted subway fare when pizza costs $3.98 per slice? Year Pizza Cost Subway Fare CPI 1960 1973 1986 1995 2002 2003 2009 2013 2015 2019 0.152 0.353 1.000 1.251 1.753 2.003 2.254 2.300 2.747 2.997 0.151 0.346 1.000 1.347 1.497 2.004 2.253 2.551 2.747 2.750 29.6 44.4 109.6 152.4 180.0 184.0 214.5 233.0 237.0 252.2 The regression equation is y=+x. (Round the y-intercept to four decimal places as needed. Round the slope to three decimal places as needed.) The best predicted subway fare when pizza costs $3.98 per slice is $ (Round to the nearest cent as needed.)
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 525 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports 232 264 361 467 537 Crash Fatality Rate 16 15.8 15.6 15.5 15 Find the equation of the regression line. y=nothing+(nothing)x (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 525 metric tons of lemon imports is nothing fatalities per 100,000 population. (Round to one decimal place as needed.) Is the prediction worthwhile? A. Since all of the requirements for finding the equation of the regression line are met, the prediction is…
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.)
Find the regression equation, letting the first variable be the predictor (x) variable. Using the sh data, where lemon imports are in metric tons and the fatality rates are per te, ouple, find the best predicted crash fatality rate for a year in which there are 450 metric tons of lemon imports. Is the prediction worthwhile? Question Viewer Lemon Imports 228 264 362 498 Crash Fatality Rate 16.1 16 15.8 15.5 526 15.1 Find the equation of the regression line. ŷ=+x (Round the y-intercept to three decimal places as needed. Round the slope to four decimal places as needed.)
Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed actress/actor ages in various years, find the best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 31 years. Is the result within 5 years of the actual Best Actor winner, whose age was 52 years? Best Actress Best Actor 27 52 O 29 37 28 37 63 43 31 32 52 45 47 62 28 62 21 43 44 45 48 40 53 31 Find the equation of the regression line. (Round the y-intercept to one decimal place as needed. Round the slope to three decimal places as needed.)
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 15.9 15.7 225 261 357 492 529 O 14.9 15.3 15.4 Round the yntercept to three decimal places as needed. Round the stope to four decimal piaces as needed.) The best predicted crash fatality rate for a year in which there are 500 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 common sense suggests there should not be much of a relationship between the two variables, the prediction does not make much sense. O B. Since all of the requirements for finding the equation of the regression line are met, the prediction is…
12 A regression was run to determine if there is a relationship between hours of study per week (xx) and the final exam scores (yy).The results of the regression were: y=ax+b a=5.531 b=23.45 r2=0.378225 r=0.615 Use this to predict the final exam score of a student who studies 8.5 hours per week, and please round your answer to a whole numbe
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 400 metric tons of lemon imports. Is the prediction worthwhile? 354 15.4 499 Lemon Imports Crash Fatality Rate 16 15.7 231 268 546 15.4 15 Find the equation of the regression line. -ロ+Ox (Round the constant three decimal places as needed. Round the coefficient to six decimal places as needed.) y%3D