An real estate analyst believes that the three main factors that influence an apartment's rent in a college town are the number of bedrooms, the number of bathrooms, and the apartment's square footage. For 40 apartments, she collects data on the rent (y, in $), the number of bedrooms (x1), the number of bathrooms (x2), and its square footage (x3). She estimates the following model as Rent = β0 + β1Bedroom + β2Bath + β3Sqft + ε. The following ANOVA table shows a portion of the regression results.

df SS MS F

Regression 3 5,694,717 1,898,239 50. 88

Residual 36 1,343,176 37,310 Total 39 7,037,893 Coefficients Standard Error t-stat p-value

Intercept 300 84. 0 3. 57 0. 001

Bedroom 226 60. 3 3. 75 0. 0006

Bath 89 55. 9 1. 59 0. 1195

Sq ft 0. 2 0. 09 2. 22 0. 0276

The slope coefficient attached to Bedroom indicates that, holding other explanatory variables constant, ________.

A. An additional bedroom increases rent, on average, by $526 B. An additional $526 in rent will lead to an additional bedroom C. An additional bedroom increases rent, on average, by $226 D. An additional $226 in rent will lead to an additional bedroom