nd 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 hich there are 425 metric tons of lemon imports. Is the prediction worthwhile? emon Imports 225 270 356 500 513 rash Fatality Rate 16 15.8 15.5 15.4 15.1 nd the equation of the regression line. 3D tound the y-intercept to three decimal places as needed. Round the slope to four decimal places as needed.)
nd 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 hich there are 425 metric tons of lemon imports. Is the prediction worthwhile? emon Imports 225 270 356 500 513 rash Fatality Rate 16 15.8 15.5 15.4 15.1 nd the equation of the regression line. 3D tound the y-intercept to three decimal places as needed. Round the slope to four decimal places as needed.)
College Algebra (MindTap Course List)
12th Edition
ISBN:9781305652231
Author:R. David Gustafson, Jeff Hughes
Publisher:R. David Gustafson, Jeff Hughes
Chapter8: Sequences, Series, And Probability
Section8.4: Geometric Sequences And Series
Problem 6SC
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Transcribed Image Text: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.)
Transcribed Image Text: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 16
225 270
356
500
513 D
15.8
15.5
15.4
15.1
Find the equation of the regression line.
ý =
(Round the y-intercept to three decimal places as needed. Round the slope to four decimal places as needed.)
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