Respuesta :
Answer:
The pattern is random, indicating a good fit for a linear model.
Step-by-step explanation:
The residuals are the difference between the actual value and the expected value.
If a linear model is a good fit, the residual pattern will be random, with most of the points close to the x-axis, and the same number of positive residuals as negative residuals.

The plot of the residual which is obtained by plotting the residual values against the independent variable is used to determine the appropriateness of a linear model for a set of data. Since, the residual plot is randomly distributed, then the linear model is a good fit (B).
- The residual plot is used to determine of a linear model is a good fit for modeling a dataset.
- When a residual plot is made, and a random distribution of points is obtained, then the linear model is a good model for the plot.
- However, if the plot shows a trend or pattern, then the linear model isn't a good fit for the data.
Therefore, since the model shows a random distribution of points, then linear model is a good fit.
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