The article develops tests to check for changes in data patterns over time, even when the starting point is random. By using specific statistical methods, the researchers were able to calculate the likelihood of detecting these changes accurately. They also compared the results to cases where the starting point was not random. Through simulations and real-world examples, the researchers demonstrated the effectiveness of their approach in identifying structural changes in data.