B.*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 ratefor a year in which there are 450 metric tons of lemon imports. Is the prediction worthwhile?Lemon ImportsCrash Fatality Rate 15.9 15.6226 262364471543 O15.315.314.8Find the equation of the regression line.y=(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 450 metric tons of lemon imports isfatalities per 100,000 population.(Round to one decimal place as needed.)Is the prediction worthwhile?Since the sample size is small, the prediction is not appropriate.Since common sense suggests there should not be much of a relationship between the two variables, the prediction does not make much sense.Since there appears to be an outlier, the prediction is not appropriate.D. Since all of the requirements for finding the equation of the regression line are met, the prediction is worthwhile.Question is complete. Tap on the red indicators to see incorrect answers.Similar QuestionAll parts showingMacBook AirF10- FSescF1F2@23%24%789delete4.YUQWtabenteGKreScaps lock> くエ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 ratefor a year in which there are 500 metric tons of lemon imports. Is the prediction worthwhile?Lemon ImportsCrash Fatality Rate 16 15.7234 262354462547 D15.415.415Find the equation of the regression line.y=+x(Round the constant three decimal places as needed. Round the coefficient to six decimal places as needed.)Enter your answer in the edit fields and then click Check Answer.Check Anrparts2 remainingClear AllMacBook Air44トト62F5F7FBescFIF2@%23%&delete23678.{QWYtabつKSDF

Answered: Image /qna-images/answer/ac9ffca2-8936-4cd2-bccb-63089303c681.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 fa for a year in which there are 500 metric tons of lemon imports. Is the prediction worthwhile? 547 D Lemon Imports Crash Fatality Rate 16 15.7 234 262 354 462 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.)

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 fa for a year in which there are 500 metric tons of lemon imports. Is the prediction worthwhile? 547 D Lemon Imports Crash Fatality Rate 16 15.7 234 262 354 462 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.)

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

The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 40 inches. Is the result close to the actual weight of 352 pounds? Use a significance level of 0.05. Chest size (inches) *Weight (pounds) 44 54 328 528 41 55 39 51 418 580 296 503 Click the icon to view the critical values of the Pearson correlation coefficient r. - What is the regression equation? x (Round to one decimal place 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? 353 480 513 Lemon Imports Crash Fatality Rate 231 263 16 15.9 15.6 15.4 15 Find the equation of the regression line. (Round the y-intercept to three decimal places as needed. Round the slope to four decimal places as needed.) Clear all Check answer View an example Get more help - Help me solve this Terms of Use Privacy Policy|Copyright © 2022 Pearson Education Inc. All Rights Reserved. 16.
1.
Find the regression equation, letting the first variable be the predictor (x) variable. Find the best predicted Nobel Laureate rate for a country that has 78.5Internet users per 100 people. How does it compare to the country's actual Nobel Laureate rate of 1.1 per 10 million people? Internet Users Per 100 Nobel Laureates80.3 5.679.6 24.277.3 8.644.6 0.183 6.138.3 0.190.1 25.189.1 7.680.1 8.983.3 12.753.2 1.976.6 12.756.8 3.379.5 1.591.5 11.493.7 25.465.1 3.157.8 1.967.9 1.794.3 31.785.3 31.387.7 1977.7 10.8
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.)
Listed below are foot lengths (mm) and heights (mm) of males. Find the regression equation, letting foot length be the predictor (x) variable. Find the best predicted height of a male with a foot length of 273.3 mm. How does the result compare to the actual height of 1776 mm? Foot Length 281.9 278.3 253.2 258.7 278.7 257.8 274.2 262.2 Height 1784.8 1771.0 1675.6 1645.9 1858.7 1710.1 1789.2 1737.4 the regression equation is y=enter your response here+enter your response herex. (Round the y-intercept to the nearest integer as needed. Round the slope to two decimal places as needed.) The best predicted height of a male with a foot length of 273.3 mm is enter your response here mm. (Round to the nearest integer as needed.)
Listed below are foot lengths (mm) and heights (mm) of males. Find the regression equation, letting foot length be the predictor (x) variable. Find the best predicted height of a male with a foot length of 272.7 mm. How does the result compare to the actual height of 1776 mm? Foot Length 282.3 277.8 252.8 258.7 279.0 258.4 274.1 261.7 Height 1785.0 1771.0 1675.7 1645.7 1859.3 1710.2 1789.2 1737.0 The regression equation is ŷ = + (x. (Round the y-intercept to the nearest integer as needed. Round the slope to two decimal places as needed.) The best predicted height of a male with a foot length of 272.7 mm is (Round to the nearest integer as needed.) How does the result compare to the actual height of 1776 mm? O A. The result is close to the actual height of 1776 mm. O B. The result is exactly the same as the actual height of 1776 mm. O C. The result is very different from the actual height of 1776 mm. O D. The result does not make sense given the context of the data. C mm.
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. Find the best predicted Nobel Laureate rate for a country that has 79.4 Internet users per 100 people. How does it compare to the country's actual Nobel Laureate rate of 1.2 per 10 million people? Internet Users Per 100 Nobel Laureates 79.3 5.6 80.5 24.2 78.8 8.7 45.2 0.1 82.5 6.2 38 0.1 90.3 25.4 88.6 7.6 80.3 9.1 83.1 12.6 53.3 1.9 76.3 12.7 56.6 3.3 78.5 1.5 91.6 11.5 93.4 25.2 65.3 3.1 57.3 1.9 68.2 1.7 94.8 31.6 85.4 31.3 86.4 19.1 78.3 10.9 2) Check Image
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…
The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 1118 796 1161 918 1103 1219 Temperature (F) 82 72.2 92.2 73 87.5 94.4