Errors
Time and again I’m thinking of the errors people commit; yes, commit, not make, I explain you the reason for my assertion.
In statistics, when we have a declared statement (”null hypothesis” we say) we have two options, haven’t we?: to accept, or to reject (actually, we could rephrase and say that rejecting is accepting the “alternative hypothesis”). So, now that comes the shocking info for those alien to statistics: when we make such a decision we are not just exposed to the error of being wrong or right, we are exposed to TWO ERRORS (brilliant, as if life wasn’t hard enough!).
First error (the “common one”) is what we would commit if our decision is to reject the declared statement when this one is right (bollocks!). It’s what we represent with an α and we’d call it “level of significance” (probability of cocking up failing to accept the right statement); usually statisticians play with levels of 5% or 1%, what means the “confidence level” (1-α) is between 95% and 99% (remember, that’s just probability!).
Second error (the “not-so-known-one”) is called “false negative” (β for friends and colleagues), and is committed when we accept the statement and what was right was the alternative one (again, damned!).
And know here comes the trick. Trying to avoid one (or reducing the probability of committing it) would increase your chances of committing the other (so, another Catch 22 in life). So, the only thing that rests us is to use the best of our knowledge and try to control one without exposing us too much to the other (that’s what statistics are for, mate!). Because, my dear colleagues, avoiding the decision, IS NOT A CHANCE!!!.
