At the 5% significance level, a p-value of 0.05 is typically treated as significant. What decision does this imply?

• A. Reject the null
• B. Fail to reject the null
• C. Not enough information
• D. Accept the null

Answer: (A)

In hypothesis testing, the decision hinges on comparing the p-value to the chosen significance level. The p-value is the probability, under the assumption that the null hypothesis is true, of obtaining results as extreme or more extreme than what was observed. If this probability is at most the significance level (here, 5%), the result is considered statistically significant and we reject the null hypothesis. A p-value of 0.05 meets this cutoff at the 5% level, so we reject the null. Remember, we don’t “accept” the null; we either reject it or fail to reject it. (Note that some conventions use a strict interpretation p < α, in which case 0.05 would not be significant, but the common standard treats 0.05 as significant at α = 0.05.)