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CPROB: A COMPUTATIONAL TOOL FOR CONDUCTING CONDITIONAL PROBABILITY ANALYSIS
Citation:
HOLLISTER, J. W., H. A. WALKER, AND J. F. PAUL. CPROB: A COMPUTATIONAL TOOL FOR CONDUCTING CONDITIONAL PROBABILITY ANALYSIS. JOURNAL OF ENVIRONMENTAL QUALITY. American Society of Agronomy, MADISON, WI, 37(Nov-Dec):2392-2396, (2008).
Impact/Purpose:
Conditional probababilty analyses, when combined with controlled experiments and other methodologies, show great promise in evaluating ecological conditions from observational data and in defining water quality and other envrinoemtal criteria.
Description:
Conditional probability analysis measures the probability of observing one event given that another event has occurred. In an environmental context, conditional probability analysis helps assess the association between an environmental contaminant (i.e. the stressor) and the ecological condition of a resource (i.e. the response). These analyses, when combined with controlled experiments and other methodologies, show great promise in evaluating ecological condition from observation data. Current applications of conditional probability analysis are largely done via scripts or cumbersome spreadsheet routines, which may prove daunting to end users and do not provide access to the underlying scripts. Combining spreadsheets with scripts eases computation through a familiar interface (i.e. Microsoft Excel) and creates a transparent process through full accessibility to the scripts. With this in mind, we developed CProb, a Microsoft Excel Add-in with R, R(D)com Server, and Visual Basic for Applications that calculates and plots scatterplots, empirical cumulative distribution functions and a conditional probability plot. In this short communication, we briefly describe conditional probability analysis, our motivation in developing a conditional probability analysis tool, its implementation as an Microsoft Excel Add-in, and illustrate its use with an example focusing on water quality criteria.