In a regression predicting sale price from living area, which is the dependent variable?
Correct Answer
B) The sale price of the property
Why this is correct: In regression, the dependent variable (Y) is the outcome you are trying to predict or explain. In an appraisal context, sale price is typically the dependent variable explained by independent variables like living area, age, etc. Why the other choices are wrong: The living area in square feet is the independent variable (predictor). The age of the improvements would be another potential independent variable. The number of comparable sales is a sample size, not a variable in the regression equation. Exam tip: Dependent = 'depends on' the others. You predict price from characteristics, not characteristics from price.
Why This Is the Correct Answer
Why this is correct: In regression, the dependent variable (Y) is the outcome you are trying to predict or explain. In an appraisal context, sale price is typically the dependent variable explained by independent variables like living area, age, etc. Why the other choices are wrong: The living area in square feet is the independent variable (predictor). The age of the improvements would be another potential independent variable. The number of comparable sales is a sample size, not a variable in the regression equation. Exam tip: Dependent = 'depends on' the others. You predict price from characteristics, not characteristics from price.
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A set of comparable sales has a mean of $250,000 and a standard deviation of $20,000. What is the coefficient of variation?
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