Question

which residual plot shows that the line of best fit is a good model?

Explanation:

Step1: Recall Residual Plot Criterion

A good line of best fit has residuals (differences between observed and predicted values) that are randomly scattered around the horizontal axis (residual = 0 line) with no obvious pattern (like curvature, increasing/decreasing spread, or a trend).

Step2: Analyze the Given Plots (From Description)

• The first plot (with scattered points around x - axis, no clear trend/pattern) vs. other plots (if any, but from the visible part, the key is random scatter). A residual plot with points randomly distributed (no trend, no clustering, no curve) indicates the linear model is appropriate. The plot where residuals are randomly scattered (not showing a pattern like a curve or increasing/decreasing) is the one where the line of best fit is a good model. Assuming the first plot (with points around the x - axis, random) is the correct one (since the other description is incomplete, but the principle is random scatter for good linear fit).

Answer:

The plot (first one described, with points randomly scattered around the residual = 0 line) shows the line of best fit is a good model. (If options were labeled, e.g., if the first plot was Option A, then "A. [Description of first plot]")