A form of hemoglobin used to test blood sugars over a period of time. ABCs of Behavior An easy method for remembering the order of behavioral components: Abscess A collection of pus around an infection. Absorb, absorption When liquids soak into a tissue they are absorbed.
In general, the forces of competition are imposing a need for more effective decision making at all levels in organizations. Progressive Approach to Modeling: Modeling for decision making involves two distinct parties, one is the decision-maker and the other is the model-builder known as the analyst.
Therefore, the analyst must be equipped with more than a set of analytical methods. Specialists in model building are often tempted to study a problem, and then go off in isolation to develop an elaborate mathematical model for use by the manager i. Unfortunately the manager may not understand this model and may either use it blindly or reject it entirely.
The specialist may feel that the manager is too ignorant and unsophisticated to appreciate the model, while the manager may feel that the specialist lives in a dream world of unrealistic assumptions and irrelevant mathematical language.
Such miscommunication can be avoided if the manager works with the specialist to develop first a simple model that provides a crude but understandable analysis.
After the manager has built up confidence in this model, additional detail and sophistication can be added, perhaps progressively only a bit at a time.
This process requires an Factors that influence course preferences among of time on the part of the manager and sincere interest on the part of the specialist in solving the manager's real problem, rather than in creating and trying to explain sophisticated models.
This progressive model building is often referred to as the bootstrapping approach and is the most important factor in determining successful implementation of a decision model. Moreover the bootstrapping approach simplifies otherwise the difficult task of model validating and verification processes.
What is a System: Systems are formed with parts put together in a particular manner in order to pursuit an objective. The relationship between the parts determines what the system does and how it functions as a whole.
Therefore, the relationship in a system are often more important than the individual parts. In general, systems that are building blocks for other systems are called subsystems The Dynamics of a System: A system that does not change is a static i.
Many of the systems we are part of are dynamic systems, which are they change over time. We refer to the way a system changes over time as the system's behavior.
And when the system's development follows a typical pattern we say the system has a behavior pattern. Whether a system is static or dynamic depends on which time horizon you choose and which variables you concentrate on. The time horizon is the time period within which you study the system.
The variables are changeable values on the system. In deterministic modelsa good decision is judged by the outcome alone. However, in probabilistic models, the decision-maker is concerned not only with the outcome value but also with the amount of risk each decision carries As an example of deterministic versus probabilistic models, consider the past and the future: Nothing we can do can change the past, but everything we do influences and changes the future, although the future has an element of uncertainty.
Managers are captivated much more by shaping the future than the history of the past.
Uncertainty is the fact of life and business; probability is the guide for a "good" life and successful business. The concept of probability occupies an important place in the decision-making process, whether the problem is one faced in business, in government, in the social sciences, or just in one's own everyday personal life.
In very few decision making situations is perfect information - all the needed facts - available. Most decisions are made in the face of uncertainty.
Probability enters into the process by playing the role of a substitute for certainty - a substitute for complete knowledge.
Probabilistic Modeling is largely based on application of statistics for probability assessment of uncontrollable events or factorsas well as risk assessment of your decision.
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