Evaluation tool selection generally

This series of articles provides several sets of tools useful for evaluating all of the aforementioned statistics at user selected confidence levels. The general statistical tools to be described are... 

Other model selection and/or discrimination tools include the posterior predictive check (PPG) and cross-validation (27,32,33). The PPG is useful for examination of the ability of the model to predict accurately certain features of the observed data (e.g., maximum concentration). Although PPG is not strictly a model discrimination technique, as it does not compare the predictive performance between models but rather evaluates the predictive performance of a single model, it does have useful characteristics that are discussed in more detail in Section 5.3.3. Gross-validation is considered accurate but is computer intensive and generally considered not to be suitable for small data sets (32). 

Graphs are an efficient means to identify trends, establish relationships, and evaluate the extent of errors or outliers. They are powerful tools to communicate ideas and concepts. The scales on the abscissa and ordinate are generally selected to cover the whole range of the data—from the origin to the maximum of the experimental data. By expanding the scales to fit the entire data range, the variation in the data becomes more evident. 

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