Answered: The regression equation is…

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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help with questions 1, 2 and 3 please ...

1. The regression equation is y=_____+____x.

(Round to one decimal place as needed.)

2.The best predicted weight for an overhead width of 2 cm is _____ kg.

(Round to one decimal place as needed.)

3. Can the prediction be correct? What is wrong with predicting the weight in this case?

A.The prediction cannot be correct because a negative weight 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. There is nothing wrong with predicting the weight in this case.

Find the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight
of a seal if the overhead width measured from a photograph is 2 cm. Can the prediction be correct? What is
wrong with predicting the weight in this case? Use a significance level of 0.05.
Overhead Width (cm)
Weight (kg)
7.8
7.5
8.6
9.3
8.1
7.7
153
171
211
213
185
174
Click the icon to view the critical values of the Pearson correlation coefficient r.
The regression equation is y =D+x.
(Round to one decimal place as needed.)

Expert Solution

Step 1

The following is the given Data :

Overhead Width = x	Weight = y
7.8	153
7.5	171
8.6	211
9.3	213
8.1	185
7.7	174

The independent variable is $x$ , and the dependent variable is $y$ . In order to compute the regression coefficients, the following table needs to be used:

	x	y	x*y	x²	y²
	7.8	153	1193.4	60.84	23409
	7.5	171	1282.5	56.25	29241
	8.6	211	1814.6	73.96	44521
	9.3	213	1980.9	86.49	45369
	8.1	185	1498.5	65.61	34225
	7.7	174	1339.8	59.29	30276
Sum =	49	1107	9109.7	402.44	207041

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