Question

A real estate appraiser explored the relationship between sales price of apartment buildings (Y) and physical condition (excellent, good, or fair). His goal is to build a regression model to predict sales price using physical condition. From the options below, which ones are the correct ways to create the indicator variables for the regression model? None of the options is correct X1 - 1 if condition is excellent, otherwise. X2 - 1 if condition is fair, otherwise. X = 1 if condition is good, otherwise. X2 = 1 if condition is fair. 0 otherwise. X3 = 1 if condition is excellent, otherwise X1 - 1 if condition is good, otherwise. X2 - 1 if condition is fair, otherwise. X1 = 1 if condition is good, otherwise. X2 - 1 if condition is excellent otherwise. X = 1 if the condition is good; X = 2 if the condition is fair; X = 3 if the condition is excellent.

Answer 1

A real estate appraiser want to build a regression model to predict sales price using physical condition (excellent, good or fair). The following is the correct way to create the Indica indicator variables for the regression model.

X1=1 if condition is good. 0 otherwise.

X2=1 if condition is fair. 0 otherwise.

X3=1 if condition is excellent. 0 otherwise.

Since the independent variable is categorical, we used indicator variables.

Indicator variable takes value 1 if it follows particular characteristic (say fair) and if does not follow given characteristic takes value 0.