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Explain about the Connecting models and data?
Perhaps the most dramatic change in quantitative environmental biology in recent years has been the burgeoning progress in the direction of rigorously matching the nonlinear, multidimensional, and spatial models employed by environmental and integrative biologists to data. Even though there is a long tradition of analyzing biological models which are parameterized with values estimated from natural systems, statistically fitting complex models to data is conceptually dissimilar and more sophisticated. Fitting a model to data and after that validating the model against independent data sets provides a direct test of the ability of a model to explain the system. Just once fitted, the model can be used to make predictions - complete with estimates of doubt in the predictions - for future changes in the system. The final goal of fitting models to data is opening up the large body of theory in environmental and integrative biology to direct test in opposition to data.
Evaluate how best to achieve the goal of fostering the integration of biology, statistics, and mathematics. What impediments stand in the way of progress? What is the best way to
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