text: The test itself is mathematically sound.  What is dicey is how you interpret the relationships it finds.\n\nBasically, you always have a possibility that the data collected, just by chance, will cause the null hypothesis of no relationship to reject: that's the alpha thing.  You select the chances of a false finding by setting your P-value for rejection.\n\nOn the other hand, ignoring the chances of missing a relationship (beta), the real problem is understanding what any relationship found might mean.  This has nothing to do with the reliability or validity of the test; it has everything to do with the clarity and rigorousness of thought of the person using it.\n\nA case in point, from my own history: ran one of those, and found an amazingly strong correlation between presence of one thing, and presense of another: doesn't matter what they were.  Bottom line: the correlation reflected the fact that both things were results of something else, that I hadn't actually recognized as being a significant variable...  until I revisited the data, years later.  Most embarassing.