The F-test is considered significant if the ratio exceeds which threshold?

• A. > 0.05
• B. > 0.10
• C. > 0.01
• D. > 0.25

Answer: (B)

In an F-test, significance is determined by the p-value associated with the observed F statistic, compared to a chosen alpha level. If the study uses a less stringent level of 0.10, then the result is considered significant whenever the p-value is below 0.10. That means the observed ratio of variances is large enough to be unlikely under the null hypothesis at that 10% level. Among typical options, 0.10 represents this looser cutoff, which is why it’s identified as the threshold for significance in this context. Remember that the exact critical F value depends on the degrees of freedom in the two variance estimates, so there isn’t a single universal F threshold; the 0.10 criterion is about the p-value cut-off, not a fixed F value. The other options reflect stricter standards (0.05 or 0.01) or an nonstandard level (0.25).