In an earlier slide, we ran a multiple linear regression model for real estate prices based on several predictors. Our fitted model was:

Price = 320394.1 + 93.1 (Living Area) - 68307 (Bedrooms) + 87743 (Bathrooms) - 14.5 (Year) - 10573.7 (Garages)

Let us consider the counterintuitive negative slope for Bedrooms, which waswith ap-value of 0.000000287. Which is the best interpretation for this coefficient andp-value, assuming that the model is valid?

• Holding the number of garages, living area, bathrooms, and year of construction fixed, increasing the number of bedrooms is associated with a lower mean price, and the association is significant.
• The predictor is not significant.
• Holding the number of garages, living area, bathrooms, and year of construction fixed, increasing the number of bedrooms is associated with a lower mean price, but the association is not significant.
• Increasing the number of bedrooms is associated with a lower mean price at a 0.05 significance level.