5. Analyzing Lines of Fit
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Make a table of the residual values and then graph them on a scatter plot.
No, see solution.
Let's begin by making a table of the residual values.
x | y | y=-0.5x-2 | y-value From Model | Residual |
---|---|---|---|---|
4 | -1 | -0.5( 4)-2 | -4 | -1-(-4)= 3 |
6 | -3 | -0.5( 6)-2 | -5 | -3-(-5)= 2 |
8 | -6 | -0.5( 8)-2 | -6 | -6-(-6)= 0 |
10 | -8 | -0.5( 10)-2 | -7 | -8-(-7)= -1 |
12 | -10 | -0.5( 12)-2 | -8 | -10-(-8)= -2 |
14 | -10 | -0.5( 14)-2 | -9 | -10-(-9)= -1 |
16 | -10 | -0.5( 16)-2 | -10 | -10-(-10)= 0 |
18 | -9 | -0.5( 18)-2 | -11 | -9-(-11)= 2 |
20 | -9 | -0.5( 20)-2 | -12 | -9-(-12)= 3 |
Now we can create a scatter plot using the given x-values and our residuals. Remember, if the model is a good fit for the data, the scatter plot will be evenly distributed above and below the x-axis. Also, there will be no apparent patterns.
This line of fit does not model the data well. It is not evenly distributed above and below the x-axis. We can see that the residual points form a U-shaped pattern, which suggests the data is not linear.