Given several sale pairs that isolate the same feature after other relevant differences are controlled, how can they support a quantitative adjustment?
Correct Answer
A) By computing the differences across several pairs
Compute the feature-related differences in several suitable pairs after accounting for other material differences, then assess their consistency, central tendency and spread. Merely averaging all sale prices or ranking superiority does not quantify the contribution. A two-point line can be fitted mathematically, but it does not provide robust independent evidence of a feature effect. More pairs help only if their quality and comparability are adequate.
Why This Is the Correct Answer
Option A is correct because computing the feature-related price differences across several suitable pairs measures the feature's effect on value. The appraiser then assesses the consistency, central tendency and spread of those differences, keeping in mind that more pairs help only if their quality and comparability are adequate.
Why the Other Options Are Wrong
Option B: By averaging the prices of all the sales involved
Option B describes averaging the prices of all the sales involved, which gives a general price level but does not isolate the feature's contribution to value.
Option C: By running a regression on a single pair of sales
Option C describes running a regression on a single pair of sales. A line can be fitted through two points mathematically, but it does not provide robust independent evidence of a feature's effect.
Option D: By ranking each pair from superior to inferior
Option D describes ranking each pair from superior to inferior, which is a qualitative comparison and does not produce a dollar or percentage adjustment.
Pair, subtract, repeat
Pair similar sales, subtract their prices to isolate the feature, and repeat across several pairs to test consistency.
How to use: Use this to recall how paired data produce a supported adjustment.
Exam Tip
Look for the answer that measures differences between paired sales; averaging prices or ranking does not quantify an adjustment.
Common Mistakes to Avoid
- -Averaging sale prices to estimate a feature's value
- -Relying on a single pair as robust proof
- -Treating qualitative ranking as a quantitative adjustment
Concept Deep Dive
Analysis
This question tests how paired sales analysis supports an adjustment. When pairs isolate the same feature after other material differences are accounted for, the price differences between paired sales indicate that feature's contribution. Computing those differences across several pairs and checking their consistency gives support for a quantitative adjustment.
Background Knowledge
Paired sales analysis compares nearly identical properties that differ mainly in one characteristic to estimate that characteristic's effect on value. Multiple pairs strengthen the conclusion if they are consistent and well matched. Ranking techniques are qualitative, while paired differences are quantitative.
Real-World Application
An appraiser finds four pairs of similar homes where one in each pair has a garage. The price differences cluster around a similar amount, so she uses that range to support her garage adjustment.
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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Previous Question
The assessment-to-sale ratios are 0.9, 0.9, 0.95, 1, 1, 1.05, 1.05. 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.
Next Question
Three sales at $500,000, $520,000 and $510,000 receive reliability weights of 0.5, 0.3 and 0.2, respectively. What is the weighted mean price, to the nearest dollar?