Real data analysis is the process of extracting meaningful insights and drawing conclusions from data collected from real-world sources. Real data analysis is fundamental in fields ranging from science to business, aiding in evidence-based decision-making and problem-solving. It often involves techniques like exploratory data analysis, hypothesis testing, and machine learning, and it plays a vital role in uncovering patterns, trends, and relationships within data to inform informed actions and decisions. We apply the localized MLE-based parameter estimates along with the relationship flowchart available in Karim et al. (2022) to detect parameter variation from a cattle growth data set studied by Kenward (1987).Â