In a study using an independent t-test with an alpha of 0.05, which result would indicate statistical significance?

In a study using an independent t-test with an alpha of 0.05, which result would indicate statistical significance?

• A. p > .05
• B. p < .05
• C. r2 > .05
• D. r2 < .05

Answer: (B)

Statistical significance in a t-test is decided by the p-value compared to the chosen alpha. With an alpha of 0.05, you declare significance when the p-value is less than 0.05. That means the observed difference between groups is unlikely to occur if the null hypothesis is true, so you reject the null and call the result statistically significant. If the p-value is greater than 0.05, you don’t have enough evidence to reject the null. R-squared values relate to variance explained and are not the criterion for significance in a t-test, though they can inform about effect size in other contexts. So the result that indicates statistical significance is the one where p is less than 0.05.

Statistical significance in a t-test is decided by the p-value compared to the chosen alpha. With an alpha of 0.05, you declare significance when the p-value is less than 0.05. That means the observed difference between groups is unlikely to occur if the null hypothesis is true, so you reject the null and call the result statistically significant. If the p-value is greater than 0.05, you don’t have enough evidence to reject the null.

R-squared values relate to variance explained and are not the criterion for significance in a t-test, though they can inform about effect size in other contexts. So the result that indicates statistical significance is the one where p is less than 0.05.