If p-value is greater than 0.05, what is the correct interpretation at the 5% significance level?

• A. Sufficient evidence to reject the null
• B. Not enough evidence to reject the null
• C. The null hypothesis is proven true
• D. The alternative hypothesis is proven true

Answer: (B)

In hypothesis testing, the p-value is the probability, assuming the null hypothesis is true, of observing data as extreme as what you saw or more so. At a 5% significance level, you reject the null if the p-value is at most 0.05. A p-value greater than 0.05 means you do not have enough evidence to reject the null at this level. It does not prove the null is true or that the alternative is false; it simply indicates the observed result isn’t statistically significant given the data. This lack of significance could come from a small sample size, low power, or a genuinely no effect. So the correct interpretation is that there is not enough evidence to reject the null at the 5% level.