Mathematical Modeling Process for Real Situations

In general, the test model is less expensive and less expensive than testing real objects and situations. Construction and research of model aircraft is certainly faster and cheaper than full scale aircraft. Likewise, the mathematical model of equation (1.1) makes it possible to quickly identify profit expectations without requiring the manager to actually manufacture and sell x units. This model also has the advantage of reducing the risks associated with the actual situation.

The model is a simplified version of the real situation. It uses mathematical symbols and relationships. It simplifies management decisions into a mathematical form that motivates and evaluates the decision-making process before making real decisions. However, careful attention must be paid to ensure that all important relationships, constraints, and variables are included in the model.

Modeling links classroom mathematics and statistics to everyday life, work, and decision-making. Modeling is the process of analyzing experiences, better understanding them, and selecting and using appropriate mathematical and statistical data to improve decision making. The number and relationships of physics, economics, public policy, social and everyday situations can be modeled using mathematical and statistical methods. When creating a mathematical model, techniques are useful for various hypotheses, investigation of the results, and comparison of predictions and data.

The core of statistical modeling is the use of mathematics to find relations between variables and to predict results. This includes a simplified mathematically defined approximation of the realistic situation and a way to predict from such an approximation. The process of creating such a mathematical reality is called modeling and the set of equations used to derive the approximation is a statistical model. To illustrate how statistical modeling works in finance, let's look at a concrete example. Evaluate the credit rating using discriminant analysis. Discriminant analysis creates a model that determines which variables of two or more groups (explanation) are different, and classifies the new entity as a usable group based on that model (prediction).

Mathematical modeling is the process of converting a physical situation into a mathematical analogy with appropriate conditions. This can be done by identifying the problem, building or choosing the appropriate model, deciding which data needs to be gathered, determining the number of variables to choose to enhance accuracy, testing the validity of the model, implementing the solution , And a model implementation. . Biological terrorism mathematical model predicts the effects of war / nuclear explosion. Mathematical modeling to prove the role of drugs in human systems Computer diagnosis of human diseases. Research on computerized system storage retrieval technology l Data processing and information management technology. Develop mathematical modeling of video games and urban planning. f) Educational technology