Binary variables represent one of two possible outcomes, while dummy variables take values of 0 or 1 to indicate the presence or absence of a categorical effect. Both types of variables are used in regression models to help analyze the influence of categorical factors on the outcome. Understanding their differences is crucial for proper application in statistical modeling.

1. What is the difference between binary and dummy variables and why are they used in regression
models?
Solution
Binary variable record one of two possible conditions or outcomes. And a dummy
variable is one that takes the values 0 or 1 to indicate the absence or presence of some categorical
effect that may be expected to shift the outcome