An appraiser wants to support a garage adjustment using regression. What does the analysis require?
Correct Answer
A) Enough sales that vary in garage capacity
Why this is correct: Regression analysis estimates the marginal contribution of a property characteristic (like a garage) by analyzing how sale prices vary with changes in that characteristic across a dataset. To estimate a reliable coefficient, there must be sufficient sales where the characteristic varies (e.g., some homes have no garage, one-car, two-car garages). If all sales are identical for that feature, its effect cannot be measured. Why the other choices are wrong: "Sales that all share an identical garage size" would prevent regression from isolating the garage's value, as there is no variation to analyze. "A separate model built for each comparable" is not how regression works; a single model is built from all data. "That the subject property be excluded entirely" is incorrect; the subject's characteristics are input into the model to predict its value. Exam tip: For any statistical analysis, variation in the data is key. No variation in a feature means you cannot measure its impact on price.
Why This Is the Correct Answer
Why this is correct: Regression analysis estimates the marginal contribution of a property characteristic (like a garage) by analyzing how sale prices vary with changes in that characteristic across a dataset. To estimate a reliable coefficient, there must be sufficient sales where the characteristic varies (e.g., some homes have no garage, one-car, two-car garages). If all sales are identical for that feature, its effect cannot be measured. Why the other choices are wrong: "Sales that all share an identical garage size" would prevent regression from isolating the garage's value, as there is no variation to analyze. "A separate model built for each comparable" is not how regression works; a single model is built from all data. "That the subject property be excluded entirely" is incorrect; the subject's characteristics are input into the model to predict its value. Exam tip: For any statistical analysis, variation in the data is key. No variation in a feature means you cannot measure its impact on price.
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