KS test for normality

This tool will perform a Kolmogorov-Smirnov (K-S) test for normality to evaluate whether the frequency distribution of values within a raster image are drawn from a Gaussian (normal) distribution. The user must specify the name of the raster image. The test can be performed optionally on the entire image or on a random sub-sample of pixel values of a user-specified size. In evaluating the significance of the test, it is important to keep in mind that given a sufficiently large sample, extremely small and non-notable differences can be found to be statistically significant. Furthermore statistical significance says nothing about the practical significance of a difference.

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The following is an example of a Python script that uses this tool:

wd = pluginHost.getWorkingDirectory()
inputFile = wd + "input.dep"
sampleSize = "1000"
args = [inputFile, sampleSize]
pluginHost.runPlugin("TestForNormality", args, False)

This is a Groovy script also using this tool:

def wd = pluginHost.getWorkingDirectory()
def inputFile = wd + "input.dep"
def sampleSize = "1000"
String[] args = [inputFile, sampleSize]
pluginHost.runPlugin("TestForNormality", args, false)