An appraiser presents a statistical analysis in a report. What must accompany it for the reader to weigh it?
Correct Answer
B) The data, period and market the analysis covers
Why this is correct: For a statistical analysis to be meaningful, the reader must know the underlying data (what was analyzed), the time period covered, and the specific market segment. This context allows judgment of relevance to the subject property and effective date. Why the other choices are wrong: The software package used is a technical detail, not essential for weighing the analysis. A statement that arithmetic was checked is about verification, not context. The credentials of the data supplier are less critical than the data itself. Exam tip: Always report the 'what, when, and where' of your statistical data.
Why This Is the Correct Answer
The data, period, and market the analysis covers are the three facts a reader needs to judge whether the result applies to this subject as of this effective date. Data identifies what was measured and whether the sample is relevant and adequate, period establishes whether the finding is current or stale relative to the effective date, and market establishes whether the sample competes with the subject at all. Supplying them lets an intended user follow the reasoning and reach the appraiser's conclusion, which is the standard a report must meet. Without them the analysis is an unverifiable assertion dressed in numbers.
Why the Other Options Are Wrong
Option A: The software package used to run the calculation
Naming the software says nothing about the inputs or the population analyzed, and the identical package will produce sound or worthless output depending on what was fed into it. Disclosing the tool can be a courtesy in a technical appendix, but it does not help a reader decide whether the result applies to the subject.
Option C: A statement that the arithmetic was checked twice
A statement that the arithmetic was checked twice speaks to clerical care, not to relevance, and the classic failure in a statistical analysis is a perfectly computed result derived from the wrong sample or period. Self-certification of accuracy also gives the reader nothing independent to evaluate.
Option D: The professional credentials of the data supplier
The data supplier's credentials may bear modestly on reliability, but a reputable source can still supply records for the wrong segment or the wrong timeframe. What matters is the content and scope of the data actually used, and the appraiser remains responsible for verifying it regardless of who provided it.
What, When, Where
Every number in a report answers to three questions: what data, when measured, where in the market. Answer all three and the reader can weigh it. Miss one and the number is decoration.
How to use: When a question asks what must accompany an analysis, choose the option describing scope and context rather than tooling, verification, or credentials.
Exam Tip
Reporting questions reward whatever lets the intended user follow and evaluate the reasoning, so pick the answer that adds context rather than the one that adds reassurance.
Common Mistakes to Avoid
- -Presenting a regression result or trend line without describing the data set behind it
- -Drawing a market conclusion from a segment that does not compete with the subject
- -Using a period that does not align with the effective date of value
- -Omitting the screening criteria that determined which transactions entered the sample
Concept Deep Dive
Analysis
This tests what makes a quantitative analysis usable to a reader, which is a reporting question rather than a statistics question. STANDARD 2 requires that a report clearly and accurately set forth the appraisal in a manner that will not be misleading and that it contain sufficient information to enable the intended users to understand the report properly. A regression output, a trend line, or a set of medians proves nothing on its own, because its meaning depends entirely on which transactions went into it, over what time frame, and from which competitive segment. Change the segment from the subject's neighborhood to the whole county, or the period from six months to five years, and the same technique produces a different answer. So the disclosures that let a reader weigh the analysis are the data set, the period covered, and the market to which it applies, along with the source of the data and any screening the appraiser applied.
Background Knowledge
You need to know that STANDARD 2 requires a report to be clear, accurate, not misleading, and to contain sufficient information for intended users to understand it properly, and that the information analyzed and the reasoning must be summarized. You should also understand that a statistical result is only as relevant as its sample, its time frame, and its market segment.
Real-World Application
You run a trend analysis to support a time adjustment and report that it covers one hundred forty-two arms-length closed sales of detached homes between eleven hundred and eighteen hundred square feet in the subject's school attendance zone, from the local multiple listing service, for the twenty-four months preceding the effective date, with foreclosure and relocation sales excluded and the exclusion criteria stated.
More Statistics Questions
A set of comparable sales has a mean of $250,000 and a standard deviation of $20,000. What is the coefficient of variation?
A property sold for $400,000 and resold three years later for $463,050 with no physical change. What compound annual rate does this indicate?
A histogram of neighborhood sale prices shows two distinct peaks. What does this most likely mean?
What does it mean to validate a regression model?
In a market study, what does a frequency distribution of sale prices show?
An appraiser includes months elapsed since each sale as a variable in a price model. What is this intended to capture?
An R-squared of 0.86 in a sales model indicates that:
Which measure would best summarize the most common lot size in a subdivision?
Paired sales analysis and regression differ mainly in that regression:
Price per square foot declines as homes get larger. What does this imply for a linear regression of price on area?
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