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Sales ComparisonEASY16.4% of exam

A multiple regression of 240 recent sales of detached homes in the subject's market area includes gross living area, lot size, age, bathrooms and garage spaces. The coefficient for gross living area is $58. What does this coefficient indicate?

Correct Answer

B) The price change for each added square foot, all else held constant

In a multiple regression, a variable's coefficient estimates its contributory value with the other variables held constant, so $58 is the price change per square foot of gross living area and can serve as a size adjustment. It is not the overall average price per square foot, which also includes land and every other feature, nor a construction cost or a measure of how much of the price variation the model explains.

Answer Options
A
The average sale price per square foot of the homes in the data
B
The price change for each added square foot, all else held constant
C
The cost to build one more square foot of living area in this market
D
The share of the variation in sale prices that living area explains

Why This Is the Correct Answer

Option B is correct because a multiple regression coefficient estimates the contributory value of one element of comparison with the other variables held constant. A GLA coefficient of $58 means each added square foot of living area adds about $58 to price.

Why the Other Options Are Wrong

Option A: The average sale price per square foot of the homes in the data

Option A treats $58 as the average sale price per square foot. Average price per square foot spreads the land, garage and every other feature over the living area, so it is usually much higher than the marginal contribution of one more square foot.

Option C: The cost to build one more square foot of living area in this market

Option C reads $58 as the cost to build a square foot. A regression of sale prices measures what buyers pay, which may differ from construction cost.

Option D: The share of the variation in sale prices that living area explains

Option D describes how much of the price variation a variable or model explains, a goodness-of-fit idea. The coefficient is a dollar amount per unit of the variable, not a share of variation.

Coefficient means dollars per unit

Read a coefficient as the price change for one more unit of that feature, everything else held still.

How to use: Use this to translate any regression coefficient into an adjustment.

Exam Tip

Do not confuse a GLA coefficient with average price per square foot; the coefficient is a marginal rate.

Common Mistakes to Avoid

  • -Treating the coefficient as average price per square foot
  • -Confusing the coefficient with a measure of model fit

Concept Deep Dive

Analysis

The question tests what a regression coefficient means. In a model with several property characteristics, each coefficient isolates the contribution of one characteristic while the others are held constant, which is why the GLA coefficient can be used as a dollars-per-square-foot adjustment.

Background Knowledge

Regression relates sale prices to property characteristics across many sales. With an adequate database, it can estimate the contributory value of selected elements of comparison without the strict similarity paired sales require.

Real-World Application

An appraiser in a tract with hundreds of similar sales runs a regression to support the size adjustment. The GLA coefficient becomes the per-square-foot rate in the grid, and the appraiser describes the data and method in the report.

regression coefficientgross living areacontributory valuemarginal ratestatistical analysis
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