What are classification and normalization?
Classification and normalization are methods that can be used to organize data, before statistical analysis, to help reduce the influences of factors other than the stressor or stressors of interest. Stressor Identification (SI) requires comparing stream segments or other sampled locations to determine whether candidate causes and effects co-occur and to develop stressor-response models from locally or regionally derived data sets. These comparisons are strongest when the variability in natural or background factors (e.g., climate, geology, stream slope) among locations is minimized. Before the effects of natural or background conditions can be minimized, the relevant variables must be identified on the basis of either ecological knowledge or data exploration. The variance in a data set due to these factors may be reduced by classification, normalization, or both.
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