Final answer:
Appropriate dummy variables for the categorical variable 'fitness' would be numerical representations such as 0 and 1 to indicate different levels of fitness, with one category serving as the reference group.
Step-by-step explanation:
When defining appropriate dummy variables for the categorical variable "fitness," one must create numerical representations for each category within the variable. The most common approach is to use binary numbers (0 and 1), where each dummy variable represents a specific category. For example:
- Dummy1 = 1 if the category is 'Low' fitness and 0 otherwise.
- Dummy2 = 1 if the category is 'High' fitness and 0 otherwise.
In this way, 'fitness' which is a categorical variable can be included in regression analysis or other statistical models that require numerical input. The correct dummy coding for the variable "fitness" would thus follow a similar structure to the first option provided, where:
- Dummy1 = 0 might represent 'Low' fitness, and
- Dummy2 = 1 might represent 'High' fitness.
It is important to note that one category typically serves as the reference group and is represented by all dummy variables being 0. In the case of a binary categorization (such as Low/High), only one dummy variable is needed because the second category is implicitly defined when the dummy is 0.