Real Data Analysis

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 ISRP along with the relationship flowchart available in Karim et al. (2022) to detect parameter variation from real data sets taken from three different domains (marketing, biology,  and epidemiology). This methodology significantly reduced the efforts involved in model fitting exercises. We believe that this method would be helpful for practitioners in the field of growth study to find the best-fitted model.