To determine the most accurate description of the residual plot based on the information about the scatterplot of cost versus distance, we need to consider how the residuals are calculated. Residuals are the differences between the observed values and the values predicted by the regression model.
-
All of the dots would fall on the residual=0 line: This would only be true if the regression model perfectly fits all data points, which is unlikely in most real-world situations.
-
There are five dots above the residual=0 line: This would indicate that there are five observations where the actual values are greater than the predicted values, and this might not reflect a balanced model.
-
There are two dots that will fall on or close to the residual=0 line: This suggests that a couple of observations are well predicted, but not representative of the overall model fit.
-
There are three dots below the residual=0 line and three dots above: This indicates a more balanced model, where some predictions are too low and some are too high, which can imply a more consistent spread of the residuals.
Given these options, if the scatterplot suggests a reasonably good fit with some variation, the description stating that there are three dots below the residual=0 line and three dots above would likely be the most accurate, as it indicates a spread of residuals above and below the line, suggesting that the predictions are not systematically biased.
1 answer