Before applying a regression-derived adjustment to a comparable, what is the best analytical step?
Correct Answer
C) Validate the model's applicability against market evidence
Assess whether the model, data, units, conditional coefficient and relevant market evidence support applying the estimated adjustment. A regression result is not automatically credible because software produced it. It may be used alongside other applicable evidence, and is not reserved for cases without paired sales. Whether additional methods are necessary depends on the appraisal problem and credibility of the available support.
Why This Is the Correct Answer
Option C is correct because before applying a regression-derived adjustment the appraiser should assess whether the model, data, units, conditional coefficient and relevant market evidence support it. Model validation is a key step in model building, and statistical analysis is one accepted way of deriving adjustments when properly supported.
Why the Other Options Are Wrong
Option A: Adopt it without analysis because the software is objective
Option A adopts the adjustment without analysis because the software is objective, but a result is not credible simply because software produced it. The model and data still require validation.
Option B: Use it without validation whenever no paired-sale evidence exists
Option B uses the adjustment without validation whenever no paired-sale evidence exists, but the lack of paired sales does not remove the need to validate. Regression may be used alongside other evidence and is not reserved for cases without paired sales.
Option D: Treat the coefficient as conclusive proof of a causal feature value
Option D treats the coefficient as conclusive proof of a causal feature value, but a regression coefficient measures a conditional association. It does not by itself prove causation or settle the adjustment.
Validate Before You Apply
Check that the model fits the market and the property before letting its coefficient become an adjustment.
How to use: Use this reminder when a question asks what to do with a regression output before using it.
Exam Tip
Prefer answers that validate statistical results against market evidence over answers that accept them because of the method or software.
Common Mistakes to Avoid
- -Assuming software output is automatically credible
- -Treating a coefficient as proof of causation
- -Skipping validation when paired-sale evidence is unavailable
Concept Deep Dive
Analysis
This question tests the step that should precede applying a regression-derived adjustment. The appraiser should validate that the model, data, units and coefficient fit the comparable and agree with relevant market evidence. Software output is not credible simply because a program produced it.
Background Knowledge
Adjustment rates can be derived through statistical analysis, modeling, paired sales or other accepted methods. Whatever the method, the appraiser must confirm that the estimate applies to the subject's market and the comparable's characteristics and is consistent with other credible evidence.
Real-World Application
An appraiser's regression on suburban sales gives a pool coefficient of $25,000. Before using it for a comparable in a different price range, the appraiser checks that the data cover that segment and that local broker feedback and paired sales are consistent.
More Statistics Questions
Sale prices are $270,000, $290,000, $300,000, $310,000, $330,000. Treat the listed observations as the complete population and divide by n when computing the standard deviation. Report to the nearest dollar.
A sales sampling frame systematically excludes a relevant part of the target market. What is the principal risk?
An appraiser estimates a market-wide price trend using only sales data from one brokerage that specializes in luxury homes, without checking how other segments are represented. What is the principal concern?
Compared with analyzing one matched sale pair for one feature, what can a suitably specified multiple regression do?
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The assessment-to-sale ratios are 0.8, 0.85, 0.9, 0.92, 0.95, 0.98, 1.02, 1.05, 1.08, 1.1, 1.15, 1.2. Calculate COD as [average absolute deviation from the median ÷ median]×100. For even n, average the two middle ratios. Report the COD as a percentage to two decimals.
Assessment-to-sale ratios are 0.94, 0.96, 0.98, 1, 1.01. Compute the arithmetic mean. Report as a decimal ratio to three places.
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