Test for symmetry - comparing multiple pairs of distributions?
Hi all, I'm doing a psychophysical study on motion direction estimation and the direction-dependence of the estimation errors.
My current problem is determining whether the perceptual bias of a motion direction is symmetrical around a cardinal direction.
So what I have are:
multiple measurements of perceptual error (dependent variable, continuous), and
several test directions (independent variable)
Because the test directions can be paired about the axis of symmetry, I thought I could test for symmetry by determining that each pair of distributions came from the same population (like an unpaired t-test). However, I do not know how to do this for multiple pairs; ANOVA compares multiple conditions against each other, but not in pairs.
Additionally, the error distributions are not normal, so it would be better to find a non-parametric test.
Maybe there is a better way of testing for symmetry than paired conditions, but I only have a basic grasp of statistics.
Any help would be much appreciated.
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Test for symmetry - comparing multiple pairs of distributions?
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