Why should an appraiser state the period a statistical summary covers?
Correct Answer
C) Conclusions apply to that period and not beyond
Why this is correct: Conclusions apply to that period and not beyond. The governing concept is temporal relevance. Statistical summaries (e.g., median price, absorption rate) describe market conditions during a specific time window. Stating the period allows the reader to assess if the data is relevant to the appraisal's effective date and avoids extrapolation beyond the analyzed period. Why the other choices are wrong: Longer periods are always more reliable than short is not necessarily true; a long period may include multiple market phases, obscuring current trends. The period determines which formula must be used is false; formulas are based on data type, not time frame. Periods under one year may not be reported at all is false; any period can be reported if properly disclosed. Exam tip: Always disclose the data collection period for any market statistic to define its applicability and limit liability.
Why This Is the Correct Answer
Why this is correct: Conclusions apply to that period and not beyond. The governing concept is temporal relevance. Statistical summaries (e.g., median price, absorption rate) describe market conditions during a specific time window. Stating the period allows the reader to assess if the data is relevant to the appraisal's effective date and avoids extrapolation beyond the analyzed period. Why the other choices are wrong: Longer periods are always more reliable than short is not necessarily true; a long period may include multiple market phases, obscuring current trends. The period determines which formula must be used is false; formulas are based on data type, not time frame. Periods under one year may not be reported at all is false; any period can be reported if properly disclosed. Exam tip: Always disclose the data collection period for any market statistic to define its applicability and limit liability.
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?
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