Probability Plots Sample Clauses

Probability Plots c) Goodness of Fit Tests.
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Probability Plots. Probability plots indicate the central tendency (median) of the data, along with their possible distribution type and variance (the steeper the plot, the smaller the COV, and the flatter the slope of the plot, the larger the COV for the data). Multiple data sets can also be plotted on the same plot (such as for different sites, different seasons, different habitats, etc.) to indicate obvious similarities (or differences) in the data sets. The values and corresponding probability positions are plotted on special normal-probability paper. When plotted on this paper, the values form a straight line if they are normally distributed. If the points do not form an acceptably straight line, they can then be plotted on log-normal probability paper (or the data observations can be log transformed and plotted on normal probability paper). If they form a straight line on the log-normal plot, then the data are log-normally distributed. If the data follow a log-normal distribution many parametric statistical tests can likely be used on the log- transformed data. In addition, most statistical methods used to compare different data sets require that the sets have the same variances. Similar variances would be indicated by generally parallel plots of the data on the probability paper. Scatter Plots. Scatter plots are typically made by plotting the primary variable (such as a water quality constituent) against a factor that may influence its value (such as time, season, flow, another constituent like suspended solids, etc.). An example of how scatter plots could be used to evaluate TCT study data is plotting measured trash generation rates as a function of the antecedent dry weather period. Scatter plots can illustrate whether that relationship appears to be linear or curved, whether different groups of data lie in separate regions of the scatter plot, and whether the variability or spread is constant over the range of data. Box and Whisker Plots. Box plots provide visual summaries of: • the center of the data (the median--the center line of the box) • the variation or spread (interquartile range--the box height) • the skewness (quartile skew--the relative size of box halves) • presence or absence of unusual values ("outside" and "far outside" values). Boxplots are particularly useful in comparing these attributes among several data sets. The relative overlapping (or separation) of different data sets on the plots can be used to identify possible groupings of the separate d...

Related to Probability Plots

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