Listed below are the overhead widths (cm) of seals measured from photographs and weights (kg) of the seals. Find the regression equation, letting the overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 1.8cm, using the regression equation. Can the prediction be correct? If not, what is wrong? Use a significance level of 0.05. Overhead Width (cm) 7.1 7.3 9.9 9.3 8.8 8.3 Weight (kg) 137 176 282 230 230 214 The regression equation is y=+x. (Round the constant to the nearest integers needed. Round the coefficient to one decimal place as needed.) The best-predicted weight for an overhead width of 1.8 cm, based on the regression equation, is: ____ kg. (Round to one decimal place as needed.) Can the prediction be correct? If not, what is wrong? A. The prediction cannot be correct because a weight of zero does not make sense and because there is not sufficient evidence of a linear correlation. B. The prediction cannot be correct because a negative weight does not make sense. The width, in this case, is beyond the scope of the available sample data. C. The prediction cannot be correct because there is not sufficient evidence of a linear correlation. The width, in this case, is beyond the scope of the available sample data. D. The prediction can be correct.

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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Question

Listed below are the overhead widths (cm) of seals measured from photographs and weights (kg) of the seals. Find the regression equation, letting the overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 1.8cm, using the regression equation. Can the prediction be correct? If not, what is wrong? Use a significance level of

0.05.

Overhead Width (cm)	7.1	7.3	9.9	9.3	8.8	8.3
Weight (kg)	137	176	282	230	230	214

The regression equation is

y=+x.

(Round the constant to the nearest integers needed. Round the coefficient to one decimal place as needed.)

The best-predicted weight for an overhead width of 1.8 cm, based on the regression equation, is: ____ kg.

(Round to one decimal place as needed.)

Can the prediction be correct? If not, what is wrong?

The prediction cannot be correct because a weight of zero does not make sense and because there is not sufficient evidence of a linear correlation.

The prediction cannot be correct because a negative weight does not make sense. The width, in this case, is beyond the scope of the available sample data.

The prediction cannot be correct because there is not sufficient evidence of a linear correlation. The width, in this case, is beyond the scope of the available sample data.

The prediction can be correct.

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