(untitled) (Applied Biological Research, 2025)
The selection of a suitable distribution for many bio-medical real data analysis is a tedious task. The general known distributions are not a good-fit, in such cases, researchers are trying for innovative distributions to overcome such situations. Since many such real data are non-symmetric, hence they do not follow normality. In this paper, we have developed a novel version of double XShanker distribution termed as ’Modified XShanker Distribution (MOXD)’ which has been described by using the weighted technique. This particular new distribution has been illustrated and explored with different statistical properties and its parameters are estimated on the basis of maximum likelihood estimation. To illustrate the predictability and flexibility of new distribution, we introduced a real lifetime biomedical data set to newly developed distribution to determine its performance over other comparable well-known distributions. Two independent real-world datasets were examined. The first dataset involved the birth weights of 130 randomly chosen new-borns from a hospital in Chennai (India). The second dataset pertained to triglyceride levels, focusing on the mean reduction (mg dL⁻¹) in triglycerides observed in 177 randomly selected patients from another Chennai hospital. These patients were monitored after taking Atorvastatin (Atorvaliq, Lipitor) continuously for 3 weeks, with triglyceride levels measured using the Cholesterol-oxidase method.