Application of mathematical modeling in thyroid stimulating hormone

Abstract

Mathematical models are to be categorized broadly as being probabilistic or newlinedeterministic. Among all situations probabilistic models are more suitable. Very newlineoften a better representation is given by considering a collection or a family of newlinerandom variables instead of a single one. Collections of random variables that are newlineindexed by a parameter such as time and space are known as stochastic process. newlineMathematical modeling problems are implicitly found in physics, newlineengineering, chemistry, computer science, biology, and even in such subjects like newlinepsychology or sociology. In recent years, more emphasis has been placed on a newlinecomplete description of the modeling cycle. newlineIn applied statistics after the group or empirical data a theoretical probability newlinedistribution is fitted in order to extract more information from the data. If the fit is newlinegood, the properties of the set of data can be approximated by the properties of the newlinedistribution. In a similar way, a real-life process has been observed to have the newlinecharacteristics process. The question is then highly desirable in understanding the newlinereal-life situation. This is especially true when the system deals with the complex. newlineMathematics has always become the major cause for the emergence of all newlinesciences. Every Science becomes vibrant in it and makes a remarkable change in the newlinefield. Biomedical science acts as a premier science with reference to predict the newlinefuture. For the continuing health of their subject, mathematicians are concerned with newlinebiology. If statisticians are not well-versed in the bio-sciences, they will not become newlinepart of the most significant and exciting scientific discoveries of all period. This uncertainty can be accommodated if we introduce probability newlinedistributions into the model in place of mathematical variables. More precisely this newlinemeans that the equations of the model will have to include random variables. Such a newlinemodel is described as Stochastic. The axiomatic method in mathematics, while newlineputting much of mathematics on solid ground, can push this modeling. newline