Question

Suppose we have quantitative variables X and Y, as well as a categorical variable named Group.

When do we use log(Group) in a model?
a. When we want an interpretation using percentage differences when comparing the groups.
b. When we want an interpretation using addition/subtraction differences when comparing the groups.
c. Both of the above.
d. None of the above.

Answer 1

Log (Group) is not appropriate to use in a model because Group is a categorical variable, and the logarithm function is meant for numerical data. Therefore, it does not provide interpretation for percentage or addition/subtraction differences when comparing groups.

Step-by-step explanation:

When analyzing a model with both quantitative variables X and Y, and a categorical variable such as Group, taking the logarithm of the Group variable, represented as log (Group), is not a standard practice because Group is not a numerical but a categorical variable. Transformations like logarithms are typically applied to quantitative variables to correct for skewness, to stabilize variance, or to make the relationships between variables more linear. Therefore, the correct answer is d. None of the above. Using log (Group) would not be appropriate for providing an interpretation using percentage or addition/subtraction differences when comparing groups, as the logarithm function is applicable to numerical data, not categorical data.