Hi, Quix... I am not sure what a “type II error” is, but that's OK.
I respect your belief in ET and I am open, but will believe
nothing till I see it. Same for many other kook to kook topics.
I am sure you know that your style does leave you open for some laughs on FR :)
Type I and type II errors
In statistics, the terms Type I error (also alpha error, or false positive) and type II error (beta error, or a false negative) are used to describe possible errors made in a statistical decision process.
When an observer makes a Type I error in evaluating a sample against its parent population, he is mistakenly thinking that a statistical difference exists when in truth there is no statistical difference (or, to put another way, the null hypothesis is true but was mistakenly rejected). For example, imagine that a pregnancy test has produced a “positive” result (indicating that the woman taking the test is pregnant); if the woman is actually not pregnant though, then we say the test produced a “false positive”.
A Type II error, or a “false negative”, is the error of failing to reject a null hypothesis when the alternative hypothesis is the true state of nature. For example, a type II error occurs if a pregnancy test reports “negative” when the woman is, in fact, pregnant.
http://en.wikipedia.org/wiki/Type_I_and_Type_II_errors