(untitled) (International Journal of Food and Nutritional Sciences, 2022)
Bayesian inference is the process of fitting a probability model to a set of data and summarizing the result by a probability distribution on the parameters of the model and on unobserved quantities such as predictions for new observations. Bayesian prediction plays a significant part in different extents of applied statistics. Bayesian approach has many benefits in statistical modelling and data analysis. It offers a system of validating the method of knowledge from data to update beliefs in accord with recent notions of knowledge synthesis. Bayesian approaches usually need less sample data to attain the same quality of implications than approaches based on sampling theory, which become very significant in the case of expensive testing processes. Bayesian inference has been used in various fields such as computer science, reliability analysis, etc.Humans, being a part of the ecosystem, have their own roles to be carried out. The human body is an integrated system, which performs different functions excretion, respiration, circulation, digestion, endocrine, intellectual and locomotion. The homeostasis is well maintained so that every organ performs its respective functions. Lungs chiefly help in the oxygenation of blood. Kidney excretes the metabolic end products. Heart pumps so that blood transfers oxygen to tissues and takes up carbon dioxide, which is then excreted through the lungs. The nervous system chiefly coordinates all the functions, makes one perceive sensations and also carry out movements. The food one eats must be digested and absorbed to give energy for one’s daily needs.Hence when any of these function fail, the entire system gets collapsed as they are closely interrelated.