Question

A national homebuilder constructs two types of homes (single-family and townhouse) in two regions of the country (Midwest and South). The homebuilder has recorded the selling price, cost of the lot, home type, and region for 168 recently sold homes.

To incorporate the type of home in regression models, develop an indicator variable. By using townhouse as the baseline type of home (the category without an indicator) and introducing an indicator for single-family, your coefficient values will align with the solution.

Answer 1

To include home type in a regression model, create an indicator variable with townhouses as the base category, assigning 0 for townhouses and 1 for single-family homes, which allows the model to differentiate between home types.

Step-by-step explanation:

To create an indicator variable for the type of home, assign a value of 0 to townhouses and a value of 1 to single-family homes. In regression analysis, this enables the model to differentiate between the two types of homes.

Assuming that townhouse is the category without an indicator (the baseline), for each home in the dataset, you would add a column with an indicator variable called 'Single_Family'. If the home type is a single-family home, this variable will have a value of 1, and if it's a townhouse, it will have a value of 0.

For example, if a particular record corresponds to a single-family home in the dataset, the 'Single_Family' indicator would be set to 1. This indicator variable is then used in the regression model to assess the impact of being a single-family home versus a townhouse on the dependent variable, which may be the selling price or another outcome of interest in the study.