Test of statistical significance uses samples to infer the statistic property of population from which the samples are taken. Two types of error, Type I (i.e., reject a true null hypothesis) and Type II errors (i.e., accept a false null hypothesis) can be made in a test of significance. Significance tests are commonly used in fisheries to identify statistical differences. Of the 6 major domestic fisheries journals, significance test methods were used in 2235 research articles within the recent 5 years (from January 2011 to April 2015), which accounted for 58.4% of all the research articles that were published in these 6 journals during the corresponding period. However, attention was only paid to the Type I errors in all these studies, and the Type II error was totally neglected. However, Type II error is not unimportant. The probability of having Type II error is often higher than that of Type I error, and sometimes the consequences are more serious for committing Type II errors. Neglecting Type II errors in fisheries is likely to result in fisheries mismanagement, consequently leading to overexploitation of fishery resources. In this study, the analyses of the Type II errors in fisheries researches were reviewed, and the potential consequence and implication of committing Type II errors in domestic fisheries researches were discussed; and the calculation method of the probability of having Type II error β (or statistical power 1-β) was described using fisheries examples. The relationships between β and several main influence factors were analyzed. We strongly suggest that Type II errors be considered and evaluated in the future fisheries research to reduce the likelihood of making serious mistakes in fisheries management.