Final answer:
In statistical analysis in regression models, the 'reference category' or 'benchmark category' is the term used to describe the category assigned the value of 0 for a dummy variable. This serves as a baseline for comparison against other categories that are assigned a value of 1. The terms 'regression dummy' or 'dummy category' are not typically used in this context.
Step-by-step explanation:
In the context of statistical analysis and especially within regression models, a dummy variable is a numerical tool used to represent categorical data, meaning it translates those categories into a form that can be provided to algorithms that traditionally require numerical input. For example, if we have a categorical variable such as gender with categories 'male' and 'female', we could represent 'male' with a dummy variable that takes a value of 1 and 'female' as 0. In this scenario, 'female' would become what is known as the reference category or benchmark category.
When constructing a regression model, the reference or benchmark category acts as the baseline against which other categories are compared. Thus, it is the category for which the dummy variable assumes a value of 0. This does not infer that it's lacking in value or less significant; rather, it is simply the standard against which other categories' coefficients in the model are judged.
Categories such as regression dummy or dummy category are typically not used to describe the category that assumes a value of 0 in the context of dummy variables. Therefore, the correct terms to refer to the category that is assigned the value of 0 for a dummy variable are either 'benchmark category' or 'reference category'.