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Listed below are the overhead widths (am) of seals measured from photographs and weights (kg) of the seals. Find the regression equation, letting the overhead width be the predictor 0) vanable Find the best predicted weight of a seal if the overhead width measured from a photograph is 2 cm, using the regression equation Can the prediction be correct? if not, what is wrong? Use a significance level of 0 05 Overhead Width (cm) Weight (ka) 7.2 73 163 98 94 8.7 84 129 261 218 211 204 The regression equation is y=-Dx (Round the y-intercept to the nearest integer as needed. Round the slope to one decimal place as needed) The best predicted weight for an overhead width of 2 cm, based on the regression equation, isNg (Round to one decmal place as needed) Can the prediction be correct? If not, what is wrong? OA The prediction cannot be corect because a negative weight does not make sense The width in this case is beyond the scope of the avatable sample data. OB The prediction cannot be correct because a weight of zero does not make sense and because there is not suffcent evidence of a inear correlation OC The prediction cannot be corect because there is not suficient evidence of a inear correlation The widh in this case is beyond the scope of the available sample data O D. The prediction can be correct

Listed below are the overhead widths (am) of seals measured from photographs and weights (kg) of the seals. Find the regression equation, letting the overhead width be the predictor 0) vanable Find the best predicted weight of a seal if the overhead width measured from a photograph is 2 cm, using the regression equation Can the prediction be correct? if not, what is wrong? Use a significance level of 0 05 Overhead Width (cm) Weight (ka) 7.2 73 163 98 94 8.7 84 129 261 218 211 204 The regression equation is y=-Dx (Round the y-intercept to the nearest integer as needed. Round the slope to one decimal place as needed) The best predicted weight for an overhead width of 2 cm, based on the regression equation, isNg (Round to one decmal place as needed) Can the prediction be correct? If not, what is wrong? OA The prediction cannot be corect because a negative weight does not make sense The width in this case is beyond the scope of the avatable sample data. OB The prediction cannot be correct because a weight of zero does not make sense and because there is not suffcent evidence of a inear correlation OC The prediction cannot be corect because there is not suficient evidence of a inear correlation The widh in this case is beyond the scope of the available sample data O D. The prediction can be correct

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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Listed below are the overhead widths (am) of seals measured from photographs and weights (kg) of the seals. Find the regression equation, letting the overhead width be the predictor 0) vanable Find the best predicted weight of a seal if the overhead width measured from a photograph is 2 am, using the regression equation Can the prediction be correct? it not, what is wrong? Use a significance level of 0 05 Overhead Width (cm) Weight (kg) 7.2 7.3 163 98 261 94 8.7 84 129 218 211 204 The regression equation is y-Ox (Round the y-intercept to the nearest integer as needed. Round the slope to one decimal place as needed) The best predicted weight for an overhead width of 2 cm, based on the regression equation, isNg (Round to one decmal place as needed) Can the prediction be correct? If not, what is wrong? OA The prediction cannot be correct because a negative weight does not make sense. The width in this case is beyond the scope of the avatable sample data OB The prediction cannot be correct because a weight of zero does not make sense and because there is not suffcient evidence of a inear correlation OC The prediction cannot be corect because there is not suficient evidence of a inear correlation The widh in this case is beyond the scope of the available sample data OD. The prediction can be correct
Transcribed Image Text:Listed below are the overhead widths (am) of seals measured from photographs and weights (kg) of the seals. Find the regression equation, letting the overhead width be the predictor 0) vanable Find the best predicted weight of a seal if the overhead width measured from a photograph is 2 am, using the regression equation Can the prediction be correct? it not, what is wrong? Use a significance level of 0 05 Overhead Width (cm) Weight (kg) 7.2 7.3 163 98 261 94 8.7 84 129 218 211 204 The regression equation is y-Ox (Round the y-intercept to the nearest integer as needed. Round the slope to one decimal place as needed) The best predicted weight for an overhead width of 2 cm, based on the regression equation, isNg (Round to one decmal place as needed) Can the prediction be correct? If not, what is wrong? OA The prediction cannot be correct because a negative weight does not make sense. The width in this case is beyond the scope of the avatable sample data OB The prediction cannot be correct because a weight of zero does not make sense and because there is not suffcient evidence of a inear correlation OC The prediction cannot be corect because there is not suficient evidence of a inear correlation The widh in this case is beyond the scope of the available sample data OD. The prediction can be correct
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