One observation in a regression has a very large residual. What should the appraiser do?
Correct Answer
D) Investigate that sale before deciding anything
Why this is correct: A large residual (the difference between the actual sale price and the model's predicted price) is a red flag that warrants investigation. The cause could be a data error, a non-arm's length transaction, or an omitted property characteristic. The appropriate action depends on the finding. Why the other choices are wrong: Deleting it without investigation could improperly bias the model. Simply accepting it without inquiry ignores a potential problem with the data or model specification. Refitting with more variables might help, but should be done after understanding the cause of the outlier. Exam tip: Investigate outliers first. Don't delete data simply to improve model fit statistics.
Why This Is the Correct Answer
Why this is correct: A large residual (the difference between the actual sale price and the model's predicted price) is a red flag that warrants investigation. The cause could be a data error, a non-arm's length transaction, or an omitted property characteristic. The appropriate action depends on the finding. Why the other choices are wrong: Deleting it without investigation could improperly bias the model. Simply accepting it without inquiry ignores a potential problem with the data or model specification. Refitting with more variables might help, but should be done after understanding the cause of the outlier. Exam tip: Investigate outliers first. Don't delete data simply to improve model fit statistics.
More appraisal-statistical-methods Questions
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An appraiser runs a regression of sale price on GLA, age, and a binary variable for 'renovated' (1 = yes, 0 = no). The estimated coefficient for 'renovated' is $18,400 with a standard error of $6,200 and a t-statistic of 2.97. Assuming a two-tailed test at Ξ± = 0.05 and 42 degrees of freedom, what conclusion is supported regarding the market's recognition of renovations?
To validate the functional form of a regression model used for adjustments, an appraiser plots residuals against predicted values and observes a clear inverted-U pattern. What does this pattern indicate, and what is the most defensible corrective action?
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