Abstract Model Paper

Decision making has become a problem in most situations. Below is an analysis of few models that are used to make decisions.

Deterministic model: It is a system used in mathematics or physics to determine the future of a given condition. In this model, no randomness takes place when determining the future state of the situation. Outcomes in this situation are determined with the help of known relationships that are expected to produce or develop similar outcomes when repeated. The problem applicable for the above model is the determination of chemical reaction. In determining chemical reaction of a certain chemical does not require any randomness thus the model suits this problem appropriately. The reason why this model is applicable in chemical reaction is due to the fact that given similar inputs at different times; the output will always remain the same. In other words, unless the inputs are changed, the expected outcomes or the outputs remain the same, (Sokolowski & Banks, 2011).

Probability Model: This is a statistical tool used to determine the probability of an occurrence of an event. It is the model that estimates basis of something using past data. In other words, probability model is a mathematical system that helps an individual in the representation of a random phenomenon. Events, sample space, and probabilities that define each event help in developing a decision based on a given mathematical problem. The problem applicable for this model includes queuing networks, hashing and distributed workload. The model is applicable in queuing networks in determining the probability of providing services to the queue. The problem is applicable in this model because the users uses past information to determine the probability of providing a service. Historical data applies in this model, and that is what helps the user determine the occurrence of an event, (Ross, 2010).

Simulation model is a mathematical analysis tool used to develop an occurrence of an event. It is a model that acts or mimics the real situation in order to determine the occurrence of a future situation. The model is based on the assumptions of a current situation and then the results are based on a future situation to happen. The problems that can be applied in this model include the financial problems and database management problems. Financial budgets are based on false assumptions with the hope to realize results when the situation is placed on the real life. The reason why financial, budget problems are applicable in this model because it is based on the assumption. Financial problems are estimates that wait the real expenditure to happen thus the model is applicable in this problem, (Sokolowski & Banks, 2011).

Discipline specific model is a behavioral analysis tool used by business and learning institutions understand behaviors of different people. It is a behavior framework that businesses use to learn and determine strategies that should be applied in working with people thought to have different behaviors in the work place. Problem applicable in this model is that of motivation. A business or firm that has motivational problems in the workplace should apply this model. Motivational problems are suitable for the model because the user of the model determine behaviors of individuals hence understand how to motivate employees, (Velten, 2009).

Reference:

Ross, M. S. (2010). Introduction to Probability Models: Academic Press

Sokolowski, A. J. & Banks, C. M. (2011). Principles of Modeling and Simulation: A Multidisciplinary Approach: John Wiley & Sons

Velten, K. (2009). Mathematical Modeling and Simulation: John Wiley & Sons

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