Examine the accompanying sample data for the variables y and x. Complete parts a through d below. 3 4 1. 7 b. Calculate the sum of squares error for the following equations: (1) y = 0.3+0.5x, (2) y = 0.4 + 1.4x, and (3) y = 0.8 + 0.5x. The sum of squares error for the equation y = 0.3+0.5x is The sum of squares error for the equation y 0.4+1.4x is The sum of squares error for the equation y 0.8+0.5x is (Round to two decimal places as needed) c Which of these equations provides the "best" fit of these data? Describe the criterion used to determine "best" fit. O A. The equation y 0.3+0.5x provides the best fit because it has the lowest sum of squares error. This criterion is called the method of least squares. O B. The equation y 0.4 +1.4x provides the best fit because it has the highest sum of squares error. This criterion is called the method of most squares. OC. The equation y 0.3+0.5x provides the best fit because it has the highest sum of squares error. This criterion is called the method of most squares. OD. The equation y 0.8+0.5x provides the best fit because it has the lowest sum of squares error. This criterion is called the method of least squares. OE. The equation y = 0.4 +1.4x provides the best fit because it has the lowest sum of squares error. This criterion is called the method of least squares. OF. The equation y 0.8+0.5x provides the best fit because it has the highest sum of squares error. This criterion is called the method of most squares.
Examine the accompanying sample data for the variables y and x. Complete parts a through d below. 3 4 1. 7 b. Calculate the sum of squares error for the following equations: (1) y = 0.3+0.5x, (2) y = 0.4 + 1.4x, and (3) y = 0.8 + 0.5x. The sum of squares error for the equation y = 0.3+0.5x is The sum of squares error for the equation y 0.4+1.4x is The sum of squares error for the equation y 0.8+0.5x is (Round to two decimal places as needed) c Which of these equations provides the "best" fit of these data? Describe the criterion used to determine "best" fit. O A. The equation y 0.3+0.5x provides the best fit because it has the lowest sum of squares error. This criterion is called the method of least squares. O B. The equation y 0.4 +1.4x provides the best fit because it has the highest sum of squares error. This criterion is called the method of most squares. OC. The equation y 0.3+0.5x provides the best fit because it has the highest sum of squares error. This criterion is called the method of most squares. OD. The equation y 0.8+0.5x provides the best fit because it has the lowest sum of squares error. This criterion is called the method of least squares. OE. The equation y = 0.4 +1.4x provides the best fit because it has the lowest sum of squares error. This criterion is called the method of least squares. OF. The equation y 0.8+0.5x provides the best fit because it has the highest sum of squares error. This criterion is called the method of most squares.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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Transcribed Image Text:Examine the accompanying sample data for the variables y and x. Complete parts a through d below.
3
4.
4.
6.
7
y
b. Calculate the sum of squares error for the following equations: (1) y = 0.3 + 0.5x, (2) y = 0.4 + 1.4x, and (3) y = 0.8 + 0.5x.
The sum of squares error for the equation y = 0.3+0.5x is
The sum of squares error for the equation y = 0.4 + 1.4x is
The sum of squares error for the equation y = 0.8 + 0.5x is
(Round to two decimal places as needed.)
c. Which of these equations provides the "best" fit of these data? Describe the criterion used to determine "best" fit.
O A. The equation y 0.3+0.5x provides the best fit because it has the lowest sum of squares error. This criterion is called the method of least squares.
O B.
The equation y = 0.4 + 1.4x provides the best fit because it has the highest sum of squares error. This criterion is called the method of most squares.
OC. The equation y = 0.3 +0.5x provides the best fit because it has the highest sum of squares error. This criterion is called the method of most squares.
O D. The equation y 0.8+0.5x provides the best fit because it has the lowest sum of squares error. This criterion is called the method of least squares.
OE.
The equation y = 0.4 +1.4x provides the best fit because it has the lowest sum of squares error. This criterion is called the method of least squares.
OF.
The equation y = 0.8 + 0.5x provides the best fit because it has the highest sum of squares error. This criterion is called the method of most squares.
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Transcribed Image Text:Examine the accompanying sample data for the variables y and x. Complete parts a through d below.
3
4
1.
1
4
5
7
a. Construct a scatter plot of these data. Describe the relationship between x and y. Choose the correct scatter plot below.
O A
OB.
C.
OD.
11-
Describe the relationship between x and y. Choose the correct answer below.
O A. There appears to be a negative linear relationship between x and y, because y increasesas x increases.
O B. There appears to be a positive linear relationship between x and y, because y decreases as x increases.
O C. There appears to be a negative linear relationship between x and y. because y decreasesas x increases.
O D. There appears to be a positive linear relationship between x and y, because y increases as x increases.
Click to select your answer(s).
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