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 "Type I" error).
如果他推断说,她感兴趣,而她其实上不感兴趣,那么他犯了假阳性的错误(统计人员所谓的“第一类”错误)。
Depending on the type of error encountered and how the procedure is coded, errors can be handled in any of several ways.
根据所遇到的错误的类型和过程的编码方式,可以使用不同的方法处理错误。
In contrast, if he infers that she is not interested when she is in fact interested, then he has made an error of false negative (what the statisticians call the "Type II" error).
相反,如果他推断,她不感兴趣,而实际上她感兴趣,那么他犯了假阴性的错误(统计学家称为“第二类”错误)。
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