In a study using an independent t-test with alpha set at 0.05, how would statistically significant results be indicated?

In a study using an independent t-test with alpha set at 0.05, how would statistically significant results be indicated?

• A. p < .05
• B. p > .05
• C. p = .05
• D. p ≤ .10

Answer: (A)

When you set alpha at 0.05, statistical significance is declared if the p-value falls below 0.05. In an independent t-test, the p-value represents the probability of obtaining a difference at least as large as the one observed if there really is no difference between the group means. If that probability is less than 5%, the result is unlikely to occur by chance, so you reject the null hypothesis and call the finding statistically significant. If the p-value is above 0.05, there isn’t enough evidence to conclude a real difference. A p-value exactly at 0.05 is a boundary; under the strict rule used here, significance is declared only when p is less than 0.05.

When you set alpha at 0.05, statistical significance is declared if the p-value falls below 0.05. In an independent t-test, the p-value represents the probability of obtaining a difference at least as large as the one observed if there really is no difference between the group means. If that probability is less than 5%, the result is unlikely to occur by chance, so you reject the null hypothesis and call the finding statistically significant. If the p-value is above 0.05, there isn’t enough evidence to conclude a real difference. A p-value exactly at 0.05 is a boundary; under the strict rule used here, significance is declared only when p is less than 0.05.