This article seems to have fallen into a common misinterpretation of the results of the study. They assume that failing to reject the null hypothesis automatica

This article seems to have fallen into a common misinterpretation of the results of the study. They assume that failing to reject the null hypothesis automatically accepts the null hypothesis. The article says "The study authors did find that, on average, women in fields like programming earn 6.6 percent less than men (a Bureau of Labor Statistics study showed that women actually earn 11 percent more, however). But that difference is not statistically significant." But that the difference is not statistically significant does not mean there is no difference. To show there is no difference, you'd need to show that the power used to run the study was sufficiently high to be confident. The correct interpretation would be "the study failed to find a significant difference in salaries between men and women, but that does not mean there isn't one." Not as exciting of a headline I guess. Update: I skimmed the study pdf and the study does not make the mistake as the article. In fact, I applaud the study for using two-tailed tests that gave them less power but more neutrality (so they were checking for gender differences in pay rather than if men were paid more than women). The study shows significant differences in pay in several professions but not engineering or math/CS.