So we make two types of errors: a typeIerror, or false positive, is believing a pattern is real when it is not; a type II error, or false negative, is not believing a pattern is real when it is.
If he infers that she is interested when she is in fact not interested, then he has made an error of false positive (what the statisticians call the "TypeI" error).