Invariance Principle

The Invariance Principle is a concept in probability and statistics that states that the behavior of certain types of random processes doesn’t depend heavily on the exact distributions involved, as long as some key characteristics are similar. In simpler terms, it means that when studying complex systems or algorithms, the overall patterns or results tend to stay consistent even if the specific details of the data change, provided some core conditions are met. This principle helps statisticians and researchers predict and analyze outcomes across different scenarios with greater confidence.