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Make a table of values to determine the residuals.
Sum for y=3x+4: 936
Sum for y=3x+4.1: 947.24
Better Line of Fit: y=3x+4
We have been given the following table.
| x | 2 | 4 | 6 | 8 |
|---|---|---|---|---|
| y | 2 | 8 | 4 | 6 |
We have also been given two possible lines of fit.
| Lines of Fit | |
|---|---|
| y=3x+4 | y=3x+4.1 |
In order to determine which line of fit is better, let's calculate the residuals for both lines.
| x | y (Actual) | y Predicted by y=3x+4 | Residual for y=3x+4 | y Predicted by y=3x+4.1 | Residual for y=3x+4.1 |
|---|---|---|---|---|---|
| 2 | 2 | y=3( 2)+4= 10 | 2- 10= -8 | y=3( 2)+4.1= 10.1 | 2- 10.1= -8.1 |
| 4 | 8 | y=3( 4)+4= 16 | 8- 16= -8 | y=3( 4)+4.1= 16.1 | 8- 16= -8.1 |
| 6 | 4 | y=3( 6)+4= 22 | 4- 22= -18 | y=3( 6)+4.1= 22.1 | 4- 22.1= -18.1 |
| 8 | 6 | y=3( 8)+4= 28 | 6- 28= -22 | y=3( 8)+4.1= 28.1 | 6- 28.1= -22.1 |
Now, we will square the residuals and find their sum s for each line so that we can compare which line is a better fit. Let's start with the line y=3x+4.
Thus, the sum of the squared residuals for y=3x+4 is 936. Next, we will continue with the line y=3x+4.1.
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The sum of the squared residuals for y=3x+4.1 is 947.24. As a result, we can say that y=3x+4.1 is the better line of fit because it has a lesser sum.