Difference between revisions of "Model"
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| − | Models can be empirically found, or derived from fundamental laws. A good model has a well-defined domain of validity, in which it leads to unambiguous, self consistent results. Ideally it is easy to evaluate. To adaption of a model to a specific problem instance is done by model parameters, which can be defined/measured independently or left as free parameters to fit the model to a realistic situation. A large number of free parameters makes it difficult to assess the validity of the model without independent knowledge. | + | Models can be empirically found, or they can be derived from fundamental laws. A good model has a well-defined domain of validity, in which it leads to unambiguous, self-consistent results. Ideally it is easy to evaluate. To adaption of a model to a specific problem instance is done by model parameters, which can be defined/measured independently or left as free parameters to fit the model to a realistic situation. A large number of free parameters makes it difficult to assess the validity of the model without independent knowledge. |
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| + | One can also make a model simply by fiddling around with the data, that is, "curve fitting" without a fundamental understanding of the phenomenon, as NASA did when studying the erosion of O-rings used in the [[space shuttle]]: | ||
| + | :A mathematical model was made to calculate erosion. This was a model based not on physical understanding but on empirical curve fitting.<ref>[http://www.ralentz.com/old/space/feynman-report.html Feynman's Appendix to the Rogers Commission Report on the Space Shuttle Challenger Accident]</ref> | ||
==References== | ==References== | ||
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Latest revision as of 04:24, September 7, 2016
In science, a model is an aid to understanding that represents an unseen or complex phenomenon.[1]
Models can be empirically found, or they can be derived from fundamental laws. A good model has a well-defined domain of validity, in which it leads to unambiguous, self-consistent results. Ideally it is easy to evaluate. To adaption of a model to a specific problem instance is done by model parameters, which can be defined/measured independently or left as free parameters to fit the model to a realistic situation. A large number of free parameters makes it difficult to assess the validity of the model without independent knowledge.
One can also make a model simply by fiddling around with the data, that is, "curve fitting" without a fundamental understanding of the phenomenon, as NASA did when studying the erosion of O-rings used in the space shuttle:
- A mathematical model was made to calculate erosion. This was a model based not on physical understanding but on empirical curve fitting.[2]
References
- ↑ Wile, Dr. Jay L. Exploring Creation With Biology. Apologia Educational Ministries, Inc. 1998
- ↑ Feynman's Appendix to the Rogers Commission Report on the Space Shuttle Challenger Accident
