In: Statistics and Probability
Curve Fitting and Linear Regression
a) Determine the linear regression equation for the measured values in the table above.
?? |
1 |
2 |
3 |
4 |
Value 1 (????) |
0 |
3 |
7 |
10 |
Value 2 (????) |
2 |
4 |
9 |
11 |
b) Plot the points and the linear regression curve.
c) Determine the Linear Correlation Coefficient (i.e., Pearson’s r) for the dataset in the table above.
a
The following data is provided:
X | Y |
0 | 2 |
3 | 4 |
7 | 9 |
10 | 11 |
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 | |
0 | 2 | 0 | 0 | 4 | |
3 | 4 | 12 | 9 | 16 | |
7 | 9 | 63 | 49 | 81 | |
10 | 11 | 110 | 100 | 121 | |
Sum = | 20 | 26 | 185 | 158 | 222 |
b)
c)
Therefore, based on this information, the sample correlation coefficient is computed as follows
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