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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
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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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. %3D voUr an ewerie)
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. %3D voUr an ewerie)
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).
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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