Question text Suppose that you have a five-point sample data set; the observations of (x, y) are given by (8, 3), (10, 3), (6, 2), (2, 0), and (2, 1).
Fit a simple linear regression model to this data by first computing the least squares estimate of the slope parameter.
Which of the following is the most accurate? Select one:
a. 0.3438
b. 0.4728
d. 0.6712
The following data are passed:
X | Y |
8 | 3 |
10 | 3 |
6 | 2 |
2 | 0 |
2 | 1 |
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 | X^{2} | Y^{2} | |
8 | 3 | 24 | 64 | 9 | |
10 | 3 | 30 | 100 | 9 | |
6 | 2 | 12 | 36 | 4 | |
2 | 0 | 0 | 4 | 0 | |
2 | 1 | 2 | 4 | 1 | |
Sum = | 28 | 9 | 68 | 208 | 23 |
Based on the above table, the following is calculated:
Therefore, based on the above calculations, the regression coefficients (the slope m, and the y-intercept n) are obtained as follows:
OPTION A is correct
Also
Therefore, we find that the regression equation is:
Let me know in comments if anything is unclear. Will reply ASAP. Please upvote!
Question text Suppose that you have a five-point sample data set; the observations of (x, y)...
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