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Sales Comparisonmedium16.4% of exam

A 'pair' shows a $22,000 gap, but closer reading reveals the cheaper sale also had dated baths. The $22,000 represents:

Correct Answer

B) The combined effect of two differences, which must be untangled

Why this is correct: In paired sales analysis, a valid pair must differ in only one significant feature. If a second difference exists (dated baths), the observed price gap ($22,000) reflects the combined value of both differences. Using this pair to extract a value for just one feature would introduce error. The analyst must either find separate data to isolate the bath adjustment or discard the pair. Why the other choices are wrong: "The isolated value of the primary feature difference alone" is incorrect because the pair is not isolated; it is contaminated. "A measurement error to discard silently" is wrong; the pair isn't an error, but it cannot be used for the intended purpose without adjustment. "Proof that paired analysis never works" is an extreme and incorrect conclusion. Exam tip: Always scrutinize paired sales for hidden differences in location, condition, or other features before accepting the price gap as a valid adjustment.

Answer Options
A
The isolated value of the primary feature difference alone
B
The combined effect of two differences, which must be untangled
C
A measurement error to discard silently
D
Proof that paired analysis never works

Why This Is the Correct Answer

The $22,000 is the combined effect of two differences, and the two must be separated before either can be used as an adjustment. Naming it as combined keeps the appraiser honest about what the data can and cannot support. The remedy is more data or a technique capable of handling multiple variables, not a guess about how to split the figure. Documenting the contamination and the resolution is what lets a reviewer evaluate the adjustment.

Why the Other Options Are Wrong

Option A: The isolated value of the primary feature difference alone

Calling the gap the isolated value of the primary feature is exactly the error the stem sets up, since isolation is precisely what this pair lacks. Doing so would inflate the primary adjustment by the unmeasured value of the bath difference and would carry that error into every comparable receiving the adjustment. The pair looks usable only until the second difference is noticed.

Option C: A measurement error to discard silently

The pair is not an error; both sales are real and both prices are presumably accurate. Discarding data silently also violates the expectation that the appraiser's analysis be transparent enough for an intended user to follow. If a pair is set aside, the reason belongs in the workfile so the reasoning can be reconstructed.

Option D: Proof that paired analysis never works

Paired analysis remains a foundational technique for deriving market-supported adjustments and is the standard answer to how an adjustment was supported. One contaminated pair says something about that pair, not about the method. Discarding a whole technique because a single application was imperfect is a category leap the evidence does not justify.

One Difference, One Number

A pair yields one number only if it contains one difference. Two differences yield one number that belongs to neither. Count the differences before you trust the gap.

How to use: In any paired-sales item, hunt the stem for a second difference in location, condition, size, age, or date. If one exists, choose the answer that calls the gap combined and requires further work.

Exam Tip

Time is the difference candidates forget to count. Two sales six months apart differ in market conditions even if the properties are identical, so pairs must be time-adjusted before the gap is attributed to a feature.

Common Mistakes to Avoid

  • -Attributing a compound gap to a single feature
  • -Failing to time-adjust pairs before comparing them
  • -Relying on one pair rather than a set showing a consistent range

Concept Deep Dive

Analysis

Paired sales analysis extracts the market's price for a single characteristic by comparing two transactions that are alike in every respect except that one characteristic. The entire inferential power of the technique rests on that isolation, because the price gap is attributed wholly to the one thing that differs. When a second difference turns up, the gap becomes a compound number containing both effects, and there is no way to know from that pair alone how the $22,000 divides between them. Assigning the full amount to the primary feature would overstate it by whatever the dated baths were worth. The disciplined responses are to find additional pairs that isolate the bath difference so it can be netted out, to use a multiple regression that can estimate several effects simultaneously, or to set the contaminated pair aside for this purpose while retaining it as general market evidence. In practice truly clean pairs are rare, which is why appraisers usually work with several pairs and look for a consistent range rather than a single number.

Background Knowledge

You need the mechanics and assumptions of paired sales analysis, particularly the requirement that pairs differ in one significant characteristic. You should also know the alternative support techniques, including grouped or matched-pair sets, multiple regression, cost-based reasoning, and income-based reasoning through rent differentials.

Real-World Application

An appraiser seeking a garage adjustment finds a pair with a $22,000 gap, then notices the cheaper home also had original baths. She locates three other pairs differing only in bath condition, establishes a bath range near $9,000, nets it out, and cross-checks the resulting garage figure against two cleaner pairs before adopting it.

paired sales analysisadjustment supportconfounded variablescontributory value
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