Type II Error (Beta Error)

In statistical inference, the error of failing to accept the alternative hypothesis tested and accepting the null hypothesis, when the alternative hypothesis is true (and the null hypothesis is false). In everyday language, we can say that it is the probability of being wrong when concluding that the research hypothesis is not supported by the data (in a sense, being “too cautious” in not trusting that the data do support the research hypothesis).